instruction
stringclasses 45
values | integer
sequencelengths 168
1.03k
| output
dict |
|---|---|---|
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
14,
14,
9,
12,
4,
5,
4,
4,
5,
4,
4,
3,
3,
3,
4,
4,
2,
3,
3,
3,
3,
2,
3,
4,
3,
3,
3,
1,
4,
2,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
4,
3,
4,
2,
3,
5,
3,
4,
5,
1,
5,
4,
3,
3,
3,
2,
1,
9,
1,
1,
9,
3,
1,
1,
5,
6,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
3,
3,
3,
3,
3,
3,
5,
5,
3,
1,
9,
4,
3,
4,
4,
2,
7,
2,
3,
4,
4,
2,
4,
1,
4,
4,
3,
1,
4,
2,
3,
3,
3,
3,
2,
2,
4,
3,
2,
1,
3,
4,
1,
1,
4,
1,
2,
2,
2,
2,
3,
3,
1,
2,
3,
3,
3,
3,
4,
4,
5,
3,
4,
4,
3,
3,
4,
4,
3,
3,
3,
4,
4,
4,
7,
2,
4,
5,
4,
5,
1,
6,
4,
4,
3,
3,
3,
3
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
11,
13
],
[
16,
22
],
[
24,
27
],
[
29,
43
],
[
45,
45
],
[
47,
48
],
[
50,
50
],
[
53,
53
],
[
56,
60
],
[
62,
63
],
[
65,
67
],
[
77,
77
],
[
80,
85
],
[
88,
89
],
[
92,
92
],
[
95,
95
],
[
97,
98
],
[
101,
101
],
[
103,
103
],
[
106,
107
],
[
109,
115
],
[
117,
120
],
[
122,
123
],
[
125,
137
],
[
141,
141
],
[
144,
145
],
[
148,
150
],
[
155,
155
],
[
160,
160
],
[
164,
167
]
]
}
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
9,
9,
11,
13,
13,
10,
9,
12,
10,
10,
9,
10,
10,
9,
16,
9,
9,
10,
9,
11,
10,
10,
11,
10,
10,
10,
10,
16,
18,
19,
16,
10,
18,
23,
18,
24,
25,
13,
16,
27,
28,
12,
21,
15,
10,
16,
10,
11,
10,
13,
12,
10,
10,
10,
10,
11,
10,
10,
12,
16,
19,
14,
15,
17,
20,
20,
16,
14,
10,
13,
24,
13,
11,
11,
11,
10,
9,
9,
9,
7,
8,
6,
5,
6,
14,
5,
4,
5,
7,
4,
5,
4,
6,
4,
3,
3,
3,
3,
4,
5,
3,
3,
4,
4,
4,
4,
5,
5,
4,
4,
4,
4,
4,
5,
2,
2,
2,
3,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
5,
6,
6,
8,
7,
4,
5,
6,
6,
6,
9,
11,
11,
12,
9,
9,
13,
13,
11,
12,
11,
9,
12,
11,
9,
10,
11,
8,
9,
11,
9,
10,
10,
9,
9,
10,
9,
9,
9,
12,
11,
21,
15,
14,
9,
35,
13,
37,
18,
19,
21,
21,
19,
9,
21,
12,
9,
9,
11,
9,
9,
10,
10,
10,
13,
19,
10,
18,
17,
22,
15,
13,
15,
13,
13,
12,
13,
12,
11,
10,
11,
10,
9,
9,
8,
7,
7,
6,
5,
5,
5,
4,
4,
5,
5,
4,
4,
4,
3,
3,
3,
4,
4,
4,
2,
4,
4,
3,
5,
6,
5,
5,
5,
4,
3,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
5,
7,
5,
6,
10,
9,
5,
7,
9,
8,
8,
6,
11,
11,
10,
10,
12,
13,
13,
11,
10,
13,
12,
9,
10,
11,
10,
10,
12,
10,
10,
10,
9,
9,
11,
9,
9,
10,
13,
9,
10,
9,
11,
10,
10,
12,
20,
19,
15,
13,
21,
22,
20,
25,
29,
20,
17,
23,
22,
11,
10,
10,
12,
11,
11,
10,
12,
18,
20,
10,
14,
11,
13,
17,
21,
19,
17,
23,
15,
12,
16,
16,
15,
15,
13,
11,
13,
14,
10,
10,
10,
8,
9,
9,
8,
6,
6,
6,
9,
6,
5,
5,
6,
5,
5,
6,
4,
4,
4,
5,
5,
4,
4,
4,
5,
13,
4,
4,
3,
5,
7,
6,
6,
8,
4,
4,
5,
5,
3,
3,
2,
2,
2,
2,
3,
3,
3,
2,
2,
3,
3,
2,
2,
4,
4,
4,
2,
2,
3,
3,
2,
2,
5,
2,
3,
2,
3,
2,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2
] | {
"1. Frame Length": "The total frame length is: 432.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
9,
9,
11,
13,
13,
10,
9,
12,
10,
10,
9,
10,
10,
9,
16,
9,
9,
10,
9,
11,
10,
10,
11,
10,
10,
10,
10,
16,
18,
19,
16,
10,
18,
23,
18,
24,
25,
13,
16,
27,
28,
12,
21,
15,
10,
16,
10,
11,
10,
13,
12,
10,
10,
10,
10,
11,
10,
10,
12,
16,
19,
14,
15,
17,
20,
20,
16,
14,
10,
13,
24,
13,
11,
11,
11,
10,
9,
9,
9,
7,
8,
6,
5,
6,
14,
5,
4,
5,
7,
4,
5,
4,
6,
4,
3,
3,
3,
3,
4,
5,
3,
3,
4,
4,
4,
4,
5,
5,
4,
4,
4,
4,
4,
5,
2,
2,
2,
3,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
5,
6,
6,
8,
7,
4,
5,
6,
6,
6,
9,
11,
11,
12,
9,
9,
13,
13,
11,
12,
11,
9,
12,
11,
9,
10,
11,
8,
9,
11,
9,
10,
10,
9,
9,
10,
9,
9,
9,
12,
11,
21,
15,
14,
9,
35,
13,
37,
18,
19,
21,
21,
19,
9,
21,
12,
9,
9,
11,
9,
9,
10,
10,
10,
13,
19,
10,
18,
17,
22,
15,
13,
15,
13,
13,
12,
13,
12,
11,
10,
11,
10,
9,
9,
8,
7,
7,
6,
5,
5,
5,
4,
4,
5,
5,
4,
4,
4,
3,
3,
3,
4,
4,
4,
2,
4,
4,
3,
5,
6,
5,
5,
5,
4,
3,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
5,
7,
5,
6,
10,
9,
5,
7,
9,
8,
8,
6,
11,
11,
10,
10,
12,
13,
13,
11,
10,
13,
12,
9,
10,
11,
10,
10,
12,
10,
10,
10,
9,
9,
11,
9,
9,
10,
13,
9,
10,
9,
11,
10,
10,
12,
20,
19,
15,
13,
21,
22,
20,
25,
29,
20,
17,
23,
22,
11,
10,
10,
12,
11,
11,
10,
12,
18,
20,
10,
14,
11,
13,
17,
21,
19,
17,
23,
15,
12,
16,
16,
15,
15,
13,
11,
13,
14,
10,
10,
10,
8,
9,
9,
8,
6,
6,
6,
9,
6,
5,
5,
6,
5,
5,
6,
4,
4,
4,
5,
5,
4,
4,
4,
5,
13,
4,
4,
3,
5,
7,
6,
6,
8,
4,
4,
5,
5,
3,
3,
2,
2,
2,
2,
3,
3,
3,
2,
2,
3,
3,
2,
2,
4,
4,
4,
2,
2,
3,
3,
2,
2,
5,
2,
3,
2,
3,
2,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
173,
173
],
[
175,
175
]
]
},
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
9,
9,
11,
13,
13,
10,
9,
12,
10,
10,
9,
10,
10,
9,
16,
9,
9,
10,
9,
11,
10,
10,
11,
10,
10,
10,
10,
16,
18,
19,
16,
10,
18,
23,
18,
24,
25,
13,
16,
27,
28,
12,
21,
15,
10,
16,
10,
11,
10,
13,
12,
10,
10,
10,
10,
11,
10,
10,
12,
16,
19,
14,
15,
17,
20,
20,
16,
14,
10,
13,
24,
13,
11,
11,
11,
10,
9,
9,
9,
7,
8,
6,
5,
6,
14,
5,
4,
5,
7,
4,
5,
4,
6,
4,
3,
3,
3,
3,
4,
5,
3,
3,
4,
4,
4,
4,
5,
5,
4,
4,
4,
4,
4,
5,
2,
2,
2,
3,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
5,
6,
6,
8,
7,
4,
5,
6,
6,
6,
9,
11,
11,
12,
9,
9,
13,
13,
11,
12,
11,
9,
12,
11,
9,
10,
11,
8,
9,
11,
9,
10,
10,
9,
9,
10,
9,
9,
9,
12,
11,
21,
15,
14,
9,
35,
13,
37,
18,
19,
21,
21,
19,
9,
21,
12,
9,
9,
11,
9,
9,
10,
10,
10,
13,
19,
10,
18,
17,
22,
15,
13,
15,
13,
13,
12,
13,
12,
11,
10,
11,
10,
9,
9,
8,
7,
7,
6,
5,
5,
5,
4,
4,
5,
5,
4,
4,
4,
3,
3,
3,
4,
4,
4,
2,
4,
4,
3,
5,
6,
5,
5,
5,
4,
3,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
5,
7,
5,
6,
10,
9,
5,
7,
9,
8,
8,
6,
11,
11,
10,
10,
12,
13,
13,
11,
10,
13,
12,
9,
10,
11,
10,
10,
12,
10,
10,
10,
9,
9,
11,
9,
9,
10,
13,
9,
10,
9,
11,
10,
10,
12,
20,
19,
15,
13,
21,
22,
20,
25,
29,
20,
17,
23,
22,
11,
10,
10,
12,
11,
11,
10,
12,
18,
20,
10,
14,
11,
13,
17,
21,
19,
17,
23,
15,
12,
16,
16,
15,
15,
13,
11,
13,
14,
10,
10,
10,
8,
9,
9,
8,
6,
6,
6,
9,
6,
5,
5,
6,
5,
5,
6,
4,
4,
4,
5,
5,
4,
4,
4,
5,
13,
4,
4,
3,
5,
7,
6,
6,
8,
4,
4,
5,
5,
3,
3,
2,
2,
2,
2,
3,
3,
3,
2,
2,
3,
3,
2,
2,
4,
4,
4,
2,
2,
3,
3,
2,
2,
5,
2,
3,
2,
3,
2,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
1
],
[
6,
6
],
[
10,
10
],
[
13,
13
],
[
15,
16
],
[
18,
18
],
[
76,
83
],
[
85,
138
],
[
142,
143
],
[
149,
149
],
[
152,
152
],
[
155,
156
],
[
158,
158
],
[
161,
162
],
[
164,
166
],
[
172,
172
],
[
181,
181
],
[
184,
185
],
[
187,
188
],
[
210,
258
],
[
260,
266
],
[
278,
278
],
[
287,
288
],
[
290,
291
],
[
294,
294
],
[
296,
296
],
[
346,
369
],
[
371,
431
]
]
}
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
2,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
3,
4,
4,
3,
3,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
2,
2,
2,
4,
4,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
3,
3,
4,
4,
3,
3,
3,
4,
3,
3,
3,
4,
4,
3,
3,
4,
4,
4,
3,
4,
3,
2,
5,
4,
2,
3,
5,
4,
3,
4,
3,
3,
3,
4,
4,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
4,
4,
3,
3,
3,
4,
4,
3,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
3,
4,
4,
3,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
4,
3,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
3,
3,
4,
4,
4,
3,
3,
3,
4,
4,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
3,
3,
3,
3,
3,
3,
4,
3,
4,
4,
2,
3,
4,
4,
3,
4,
3,
3,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
4,
4,
4,
4,
3,
4,
4,
3,
3,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
3,
3,
4,
4,
4,
3,
4,
4,
3,
3,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
4,
5,
4,
4,
4,
4,
4,
5,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
4,
4,
4,
4,
4,
4,
5,
4,
4,
4,
5,
4,
4,
4,
4,
4,
4,
3,
6,
5,
3,
4,
4,
4,
4,
3,
4,
6,
4,
3,
4,
6,
5,
4,
3,
4,
5,
4,
4,
4,
4,
4,
5,
4,
4,
4,
4,
4,
5,
3,
4,
6,
4,
3,
4,
5,
4,
3,
5,
5,
4,
4,
5,
4,
4,
4,
4,
4,
3,
3,
4,
4,
5,
4,
4,
3,
4,
4,
4,
4,
3,
3,
4,
5,
3,
3,
3,
3,
4,
3,
3,
3,
4,
4,
4,
3,
3,
4,
3,
3,
3,
3,
3,
3,
4,
4,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
3,
4,
4,
3,
3,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
5,
5,
3,
4,
3,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
4,
3,
3,
3,
3,
3,
4,
3,
3,
3,
4,
4,
3,
3,
4,
4,
4,
4,
3,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
4,
3,
3,
3,
4,
3,
3,
4,
4,
3,
4,
4,
3,
3,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
] | {
"1. Frame Length": "The total frame length is: 1033.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
2,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
3,
4,
4,
3,
3,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
2,
2,
2,
4,
4,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
3,
3,
4,
4,
3,
3,
3,
4,
3,
3,
3,
4,
4,
3,
3,
4,
4,
4,
3,
4,
3,
2,
5,
4,
2,
3,
5,
4,
3,
4,
3,
3,
3,
4,
4,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
4,
4,
3,
3,
3,
4,
4,
3,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
3,
4,
4,
3,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
4,
3,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
3,
3,
4,
4,
4,
3,
3,
3,
4,
4,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
3,
3,
3,
3,
3,
3,
4,
3,
4,
4,
2,
3,
4,
4,
3,
4,
3,
3,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
4,
4,
4,
4,
3,
4,
4,
3,
3,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
3,
3,
4,
4,
4,
3,
4,
4,
3,
3,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
4,
5,
4,
4,
4,
4,
4,
5,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
4,
4,
4,
4,
4,
4,
5,
4,
4,
4,
5,
4,
4,
4,
4,
4,
4,
3,
6,
5,
3,
4,
4,
4,
4,
3,
4,
6,
4,
3,
4,
6,
5,
4,
3,
4,
5,
4,
4,
4,
4,
4,
5,
4,
4,
4,
4,
4,
5,
3,
4,
6,
4,
3,
4,
5,
4,
3,
5,
5,
4,
4,
5,
4,
4,
4,
4,
4,
3,
3,
4,
4,
5,
4,
4,
3,
4,
4,
4,
4,
3,
3,
4,
5,
3,
3,
3,
3,
4,
3,
3,
3,
4,
4,
4,
3,
3,
4,
3,
3,
3,
3,
3,
3,
4,
4,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
3,
4,
4,
3,
3,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
5,
5,
3,
4,
3,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
4,
3,
3,
3,
3,
3,
4,
3,
3,
3,
4,
4,
3,
3,
4,
4,
4,
4,
3,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
4,
3,
3,
3,
4,
3,
3,
4,
4,
3,
4,
4,
3,
3,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
218,
218
],
[
222,
222
],
[
533,
533
],
[
539,
539
],
[
551,
552
],
[
566,
566
],
[
573,
573
],
[
577,
577
],
[
585,
586
],
[
594,
594
],
[
598,
599
],
[
603,
603
],
[
609,
609
],
[
615,
615
],
[
618,
618
],
[
622,
622
],
[
625,
626
],
[
629,
629
],
[
639,
639
],
[
650,
650
],
[
737,
738
]
]
},
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
2,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
3,
4,
4,
3,
3,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
2,
2,
2,
4,
4,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
3,
3,
4,
4,
3,
3,
3,
4,
3,
3,
3,
4,
4,
3,
3,
4,
4,
4,
3,
4,
3,
2,
5,
4,
2,
3,
5,
4,
3,
4,
3,
3,
3,
4,
4,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
4,
4,
3,
3,
3,
4,
4,
3,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
3,
4,
4,
3,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
4,
3,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
3,
3,
4,
4,
4,
3,
3,
3,
4,
4,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
3,
3,
3,
3,
3,
3,
4,
3,
4,
4,
2,
3,
4,
4,
3,
4,
3,
3,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
4,
4,
4,
4,
3,
4,
4,
3,
3,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
3,
3,
4,
4,
4,
3,
4,
4,
3,
3,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
4,
5,
4,
4,
4,
4,
4,
5,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
4,
4,
4,
4,
4,
4,
5,
4,
4,
4,
5,
4,
4,
4,
4,
4,
4,
3,
6,
5,
3,
4,
4,
4,
4,
3,
4,
6,
4,
3,
4,
6,
5,
4,
3,
4,
5,
4,
4,
4,
4,
4,
5,
4,
4,
4,
4,
4,
5,
3,
4,
6,
4,
3,
4,
5,
4,
3,
5,
5,
4,
4,
5,
4,
4,
4,
4,
4,
3,
3,
4,
4,
5,
4,
4,
3,
4,
4,
4,
4,
3,
3,
4,
5,
3,
3,
3,
3,
4,
3,
3,
3,
4,
4,
4,
3,
3,
4,
3,
3,
3,
3,
3,
3,
4,
4,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
3,
4,
4,
3,
3,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
5,
5,
3,
4,
3,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
4,
3,
3,
3,
3,
3,
4,
3,
3,
3,
4,
4,
3,
3,
4,
4,
4,
4,
3,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
4,
3,
3,
3,
4,
3,
3,
4,
4,
3,
4,
4,
3,
3,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
25,
25
],
[
33,
33
],
[
157,
159
],
[
164,
164
],
[
217,
217
],
[
220,
220
],
[
415,
415
],
[
784,
784
],
[
817,
817
],
[
1006,
1006
]
]
}
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
6,
6,
6,
6,
5,
6,
6,
6,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
5,
6,
7,
6,
6,
6,
6,
6,
6,
5,
6,
7,
6,
6,
6,
6,
6,
6,
6,
5,
6,
6,
5,
5,
6,
6,
6,
6,
6,
5,
5,
6,
5,
5,
6,
6,
4,
5,
7,
6,
5,
6,
5,
5,
5,
5,
5,
6,
5,
5,
6,
5,
4,
5,
5,
6,
5,
5,
5,
6,
5,
4,
6,
5,
5,
6,
5,
5,
6,
6,
6,
5,
4,
4,
8,
7,
4,
7,
5,
6,
7,
5,
4,
7,
7,
5,
5,
6,
5,
5,
5,
5,
6,
6,
5,
5,
5,
5,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
6,
6,
5,
5,
5,
5,
6,
4,
5,
6,
5,
6,
5,
5,
5,
5,
6,
6,
5,
7,
8,
6,
5,
7,
7,
6,
6,
6,
7,
7,
6,
6,
6,
7,
6,
6,
6,
7,
7,
5,
6,
6,
5,
5,
5,
6,
7,
5,
5,
9,
7,
6,
7,
7,
6,
6,
8,
7,
5,
6,
8,
7,
8,
7,
6,
10,
8,
6,
8,
7,
8,
14,
5,
6,
8,
9,
9,
8,
8,
7,
10,
9,
8,
8,
10,
9,
8,
7,
8,
10,
10,
10,
11,
10,
8,
9,
12,
13,
7,
12,
10,
7,
11,
21,
23,
11,
12,
13,
11,
10,
9,
13,
13,
11,
11,
11,
11,
12,
13,
11,
11,
10,
10,
14,
13,
15,
11,
9,
13,
15,
12,
12,
13,
12,
12,
11,
12,
11,
12,
12,
12,
12,
13,
12,
9,
11,
13,
14,
11,
11,
10,
10,
14,
13,
10,
12,
11,
12,
12,
12,
12,
12,
11,
10,
13,
12,
12,
11,
11,
11,
10,
10,
13,
12,
10,
11,
15,
12,
10,
12,
12,
12,
11,
11,
11,
9,
20,
12,
13,
12,
10,
9,
12,
10,
13,
10,
10,
11,
10,
10,
11,
10,
11,
12,
10,
9,
9,
10,
10,
11,
10,
7,
8,
10,
9,
12,
10,
7,
8,
10,
8,
9,
10,
10,
7,
7,
9,
8,
8,
9,
7,
7,
10,
7,
6,
9,
27,
16,
6,
9,
9,
8,
7,
7,
8,
8,
8,
8,
7,
8,
7,
7,
7,
7,
8,
9,
10,
10,
5,
7,
8,
5,
10,
8,
7,
9,
8,
7,
6,
6,
9,
9,
6,
6,
8,
7,
6,
6,
7,
7,
7,
6,
6,
6,
6,
5,
7,
9,
6,
6,
6,
6,
6,
5,
5,
6,
5,
5,
6,
5,
8,
6,
6,
6,
7,
6,
5,
6,
7,
7,
6,
6,
5,
7,
7
] | {
"1. Frame Length": "The total frame length is: 475.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
6,
6,
6,
6,
5,
6,
6,
6,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
5,
6,
7,
6,
6,
6,
6,
6,
6,
5,
6,
7,
6,
6,
6,
6,
6,
6,
6,
5,
6,
6,
5,
5,
6,
6,
6,
6,
6,
5,
5,
6,
5,
5,
6,
6,
4,
5,
7,
6,
5,
6,
5,
5,
5,
5,
5,
6,
5,
5,
6,
5,
4,
5,
5,
6,
5,
5,
5,
6,
5,
4,
6,
5,
5,
6,
5,
5,
6,
6,
6,
5,
4,
4,
8,
7,
4,
7,
5,
6,
7,
5,
4,
7,
7,
5,
5,
6,
5,
5,
5,
5,
6,
6,
5,
5,
5,
5,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
6,
6,
5,
5,
5,
5,
6,
4,
5,
6,
5,
6,
5,
5,
5,
5,
6,
6,
5,
7,
8,
6,
5,
7,
7,
6,
6,
6,
7,
7,
6,
6,
6,
7,
6,
6,
6,
7,
7,
5,
6,
6,
5,
5,
5,
6,
7,
5,
5,
9,
7,
6,
7,
7,
6,
6,
8,
7,
5,
6,
8,
7,
8,
7,
6,
10,
8,
6,
8,
7,
8,
14,
5,
6,
8,
9,
9,
8,
8,
7,
10,
9,
8,
8,
10,
9,
8,
7,
8,
10,
10,
10,
11,
10,
8,
9,
12,
13,
7,
12,
10,
7,
11,
21,
23,
11,
12,
13,
11,
10,
9,
13,
13,
11,
11,
11,
11,
12,
13,
11,
11,
10,
10,
14,
13,
15,
11,
9,
13,
15,
12,
12,
13,
12,
12,
11,
12,
11,
12,
12,
12,
12,
13,
12,
9,
11,
13,
14,
11,
11,
10,
10,
14,
13,
10,
12,
11,
12,
12,
12,
12,
12,
11,
10,
13,
12,
12,
11,
11,
11,
10,
10,
13,
12,
10,
11,
15,
12,
10,
12,
12,
12,
11,
11,
11,
9,
20,
12,
13,
12,
10,
9,
12,
10,
13,
10,
10,
11,
10,
10,
11,
10,
11,
12,
10,
9,
9,
10,
10,
11,
10,
7,
8,
10,
9,
12,
10,
7,
8,
10,
8,
9,
10,
10,
7,
7,
9,
8,
8,
9,
7,
7,
10,
7,
6,
9,
27,
16,
6,
9,
9,
8,
7,
7,
8,
8,
8,
8,
7,
8,
7,
7,
7,
7,
8,
9,
10,
10,
5,
7,
8,
5,
10,
8,
7,
9,
8,
7,
6,
6,
9,
9,
6,
6,
8,
7,
6,
6,
7,
7,
7,
6,
6,
6,
6,
5,
7,
9,
6,
6,
6,
6,
6,
5,
5,
6,
5,
5,
6,
5,
8,
6,
6,
6,
7,
6,
5,
6,
7,
7,
6,
6,
5,
7,
7
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
264,
264
],
[
396,
396
]
]
},
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
6,
6,
6,
6,
5,
6,
6,
6,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
5,
6,
7,
6,
6,
6,
6,
6,
6,
5,
6,
7,
6,
6,
6,
6,
6,
6,
6,
5,
6,
6,
5,
5,
6,
6,
6,
6,
6,
5,
5,
6,
5,
5,
6,
6,
4,
5,
7,
6,
5,
6,
5,
5,
5,
5,
5,
6,
5,
5,
6,
5,
4,
5,
5,
6,
5,
5,
5,
6,
5,
4,
6,
5,
5,
6,
5,
5,
6,
6,
6,
5,
4,
4,
8,
7,
4,
7,
5,
6,
7,
5,
4,
7,
7,
5,
5,
6,
5,
5,
5,
5,
6,
6,
5,
5,
5,
5,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
6,
6,
5,
5,
5,
5,
6,
4,
5,
6,
5,
6,
5,
5,
5,
5,
6,
6,
5,
7,
8,
6,
5,
7,
7,
6,
6,
6,
7,
7,
6,
6,
6,
7,
6,
6,
6,
7,
7,
5,
6,
6,
5,
5,
5,
6,
7,
5,
5,
9,
7,
6,
7,
7,
6,
6,
8,
7,
5,
6,
8,
7,
8,
7,
6,
10,
8,
6,
8,
7,
8,
14,
5,
6,
8,
9,
9,
8,
8,
7,
10,
9,
8,
8,
10,
9,
8,
7,
8,
10,
10,
10,
11,
10,
8,
9,
12,
13,
7,
12,
10,
7,
11,
21,
23,
11,
12,
13,
11,
10,
9,
13,
13,
11,
11,
11,
11,
12,
13,
11,
11,
10,
10,
14,
13,
15,
11,
9,
13,
15,
12,
12,
13,
12,
12,
11,
12,
11,
12,
12,
12,
12,
13,
12,
9,
11,
13,
14,
11,
11,
10,
10,
14,
13,
10,
12,
11,
12,
12,
12,
12,
12,
11,
10,
13,
12,
12,
11,
11,
11,
10,
10,
13,
12,
10,
11,
15,
12,
10,
12,
12,
12,
11,
11,
11,
9,
20,
12,
13,
12,
10,
9,
12,
10,
13,
10,
10,
11,
10,
10,
11,
10,
11,
12,
10,
9,
9,
10,
10,
11,
10,
7,
8,
10,
9,
12,
10,
7,
8,
10,
8,
9,
10,
10,
7,
7,
9,
8,
8,
9,
7,
7,
10,
7,
6,
9,
27,
16,
6,
9,
9,
8,
7,
7,
8,
8,
8,
8,
7,
8,
7,
7,
7,
7,
8,
9,
10,
10,
5,
7,
8,
5,
10,
8,
7,
9,
8,
7,
6,
6,
9,
9,
6,
6,
8,
7,
6,
6,
7,
7,
7,
6,
6,
6,
6,
5,
7,
9,
6,
6,
6,
6,
6,
5,
5,
6,
5,
5,
6,
5,
8,
6,
6,
6,
7,
6,
5,
6,
7,
7,
6,
6,
5,
7,
7
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
208
],
[
210,
224
],
[
226,
230
],
[
232,
234
],
[
237,
239
],
[
242,
243
],
[
246,
248
],
[
254,
254
],
[
258,
258
],
[
261,
261
],
[
371,
372
],
[
377,
378
],
[
380,
380
],
[
384,
385
],
[
387,
388
],
[
390,
391
],
[
393,
394
],
[
398,
398
],
[
401,
414
],
[
418,
421
],
[
423,
424
],
[
426,
429
],
[
432,
446
],
[
448,
474
]
]
}
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
9,
9,
9,
9,
9,
8,
10,
8,
8,
12,
8,
9,
7,
10,
10,
8,
10,
8,
9,
10,
9,
9,
10,
9,
9,
8,
9,
9,
9,
9,
9,
9,
9,
9,
10,
9,
8,
10,
9,
8,
9,
9,
9,
10,
9,
9,
9,
9,
10,
8,
10,
8,
9,
9,
8,
9,
8,
8,
10,
8,
9,
7,
8,
10,
9,
8,
8,
8,
9,
9,
8,
8,
8,
8,
9,
9,
8,
8,
15,
6,
5,
11,
10,
6,
8,
10,
9,
6,
8,
9,
8,
7,
7,
8,
4,
15,
12,
18,
14,
12,
15,
8,
6,
12,
6,
12,
18,
19,
12,
4,
11,
14,
4,
16,
16,
11,
15,
14,
14,
14,
15,
14,
9,
10,
15,
15,
14,
10,
13,
18,
13,
12,
12,
12,
13,
14,
14,
9,
11,
17,
13,
12,
13,
11,
13,
14,
11,
13,
13,
11,
13,
11,
13,
13,
12,
10,
12,
16,
14,
11,
12,
13,
11,
12,
13,
10,
11,
14,
11,
9,
11,
14,
10,
8,
10,
14,
11,
8,
12,
11,
6,
13,
12,
10,
10,
10,
9,
10,
11,
10,
11,
10,
9,
10,
11,
8,
7,
13,
14,
2,
9,
15,
8,
6,
11,
5,
3,
16,
12,
10,
9,
7,
8,
10,
8,
8,
10,
10,
8,
8,
9,
10,
11,
9,
9,
11,
12,
10,
10,
11,
10,
9,
12,
12,
9,
9,
9,
8,
30,
16,
12,
7,
15,
9,
10,
10,
10,
11,
9,
8,
7,
7,
11,
10,
7,
10,
9,
7,
8,
7,
7,
8,
7,
8,
7,
7,
6,
6,
7,
7,
5,
6,
5,
5,
6,
5,
4,
6,
6,
4,
3,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
5,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4
] | {
"1. Frame Length": "The total frame length is: 364.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
9,
9,
9,
9,
9,
8,
10,
8,
8,
12,
8,
9,
7,
10,
10,
8,
10,
8,
9,
10,
9,
9,
10,
9,
9,
8,
9,
9,
9,
9,
9,
9,
9,
9,
10,
9,
8,
10,
9,
8,
9,
9,
9,
10,
9,
9,
9,
9,
10,
8,
10,
8,
9,
9,
8,
9,
8,
8,
10,
8,
9,
7,
8,
10,
9,
8,
8,
8,
9,
9,
8,
8,
8,
8,
9,
9,
8,
8,
15,
6,
5,
11,
10,
6,
8,
10,
9,
6,
8,
9,
8,
7,
7,
8,
4,
15,
12,
18,
14,
12,
15,
8,
6,
12,
6,
12,
18,
19,
12,
4,
11,
14,
4,
16,
16,
11,
15,
14,
14,
14,
15,
14,
9,
10,
15,
15,
14,
10,
13,
18,
13,
12,
12,
12,
13,
14,
14,
9,
11,
17,
13,
12,
13,
11,
13,
14,
11,
13,
13,
11,
13,
11,
13,
13,
12,
10,
12,
16,
14,
11,
12,
13,
11,
12,
13,
10,
11,
14,
11,
9,
11,
14,
10,
8,
10,
14,
11,
8,
12,
11,
6,
13,
12,
10,
10,
10,
9,
10,
11,
10,
11,
10,
9,
10,
11,
8,
7,
13,
14,
2,
9,
15,
8,
6,
11,
5,
3,
16,
12,
10,
9,
7,
8,
10,
8,
8,
10,
10,
8,
8,
9,
10,
11,
9,
9,
11,
12,
10,
10,
11,
10,
9,
12,
12,
9,
9,
9,
8,
30,
16,
12,
7,
15,
9,
10,
10,
10,
11,
9,
8,
7,
7,
11,
10,
7,
10,
9,
7,
8,
7,
7,
8,
7,
8,
7,
7,
6,
6,
7,
7,
5,
6,
5,
5,
6,
5,
4,
6,
6,
4,
3,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
5,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
238,
238
]
]
},
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
9,
9,
9,
9,
9,
8,
10,
8,
8,
12,
8,
9,
7,
10,
10,
8,
10,
8,
9,
10,
9,
9,
10,
9,
9,
8,
9,
9,
9,
9,
9,
9,
9,
9,
10,
9,
8,
10,
9,
8,
9,
9,
9,
10,
9,
9,
9,
9,
10,
8,
10,
8,
9,
9,
8,
9,
8,
8,
10,
8,
9,
7,
8,
10,
9,
8,
8,
8,
9,
9,
8,
8,
8,
8,
9,
9,
8,
8,
15,
6,
5,
11,
10,
6,
8,
10,
9,
6,
8,
9,
8,
7,
7,
8,
4,
15,
12,
18,
14,
12,
15,
8,
6,
12,
6,
12,
18,
19,
12,
4,
11,
14,
4,
16,
16,
11,
15,
14,
14,
14,
15,
14,
9,
10,
15,
15,
14,
10,
13,
18,
13,
12,
12,
12,
13,
14,
14,
9,
11,
17,
13,
12,
13,
11,
13,
14,
11,
13,
13,
11,
13,
11,
13,
13,
12,
10,
12,
16,
14,
11,
12,
13,
11,
12,
13,
10,
11,
14,
11,
9,
11,
14,
10,
8,
10,
14,
11,
8,
12,
11,
6,
13,
12,
10,
10,
10,
9,
10,
11,
10,
11,
10,
9,
10,
11,
8,
7,
13,
14,
2,
9,
15,
8,
6,
11,
5,
3,
16,
12,
10,
9,
7,
8,
10,
8,
8,
10,
10,
8,
8,
9,
10,
11,
9,
9,
11,
12,
10,
10,
11,
10,
9,
12,
12,
9,
9,
9,
8,
30,
16,
12,
7,
15,
9,
10,
10,
10,
11,
9,
8,
7,
7,
11,
10,
7,
10,
9,
7,
8,
7,
7,
8,
7,
8,
7,
7,
6,
6,
7,
7,
5,
6,
5,
5,
6,
5,
4,
6,
6,
4,
3,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
5,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
12,
12
],
[
61,
61
],
[
79,
80
],
[
83,
83
],
[
87,
87
],
[
91,
92
],
[
94,
94
],
[
102,
102
],
[
104,
104
],
[
109,
109
],
[
112,
112
],
[
180,
180
],
[
196,
196
],
[
199,
199
],
[
203,
203
],
[
205,
206
],
[
211,
211
],
[
241,
241
],
[
250,
251
],
[
254,
254
],
[
257,
257
],
[
259,
260
],
[
262,
262
],
[
264,
363
]
]
}
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
7,
8,
8,
8,
8,
8,
8,
7,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
8,
8,
8,
8,
9,
9,
8,
8,
7,
8,
7,
6,
6,
6,
11,
7,
7,
9,
9,
10,
10,
17,
18,
18,
17,
11,
5,
7,
5,
7,
17,
19,
27,
8,
9,
10,
10,
10,
11,
11,
10,
12,
11,
9,
10,
9,
9,
9,
9,
10,
11,
10,
10,
8,
6,
6,
5,
7,
5,
6,
5,
8,
13,
15,
19,
21,
17,
12,
8,
6,
6,
8,
12,
9,
10,
12,
14,
14,
14,
13,
11,
10,
8,
6,
6,
5,
5,
5,
6,
7,
8,
9,
6,
6,
11,
16,
13,
6,
6,
7,
10,
6,
7,
6,
7,
14,
10,
13,
15,
20,
28,
21,
7,
6,
11,
11,
9,
7,
17,
8,
8,
10,
9,
8,
8,
8,
9,
10,
11,
10,
8,
10,
7,
12,
11,
10,
9,
9,
9,
9,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
8,
7,
7,
8,
8,
7,
8,
8,
9,
11,
11,
9,
9,
8,
6,
7,
8,
9,
9,
7,
5,
5,
6,
11,
4,
14,
13,
11,
23,
17,
13,
12,
6,
9,
12,
10,
15,
11,
9,
11,
10,
10,
8,
7,
8,
8,
7,
8,
7,
7,
7,
3,
7,
9,
8,
6,
6,
7,
7,
6,
9,
7,
7,
7,
7,
9,
6,
9,
6,
9,
5,
12,
7,
11,
8,
7,
8,
7,
8,
9,
8,
9,
7,
12,
6,
10,
8,
8,
9,
9,
8,
10,
8,
8,
8,
8,
8,
8,
9,
9,
9,
8,
8,
8,
10,
7,
9,
8,
8,
11,
8,
8,
9,
9,
9,
8,
9,
9,
9,
9,
7,
10,
9,
9,
9,
9,
8,
8,
8,
8,
9,
8,
7,
8,
9,
9,
8,
7,
9,
8,
8,
8,
9,
8,
8,
8,
8,
8,
9,
8,
8,
8,
8,
8,
9,
6,
6
] | {
"1. Frame Length": "The total frame length is: 442.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
7,
8,
8,
8,
8,
8,
8,
7,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
8,
8,
8,
8,
9,
9,
8,
8,
7,
8,
7,
6,
6,
6,
11,
7,
7,
9,
9,
10,
10,
17,
18,
18,
17,
11,
5,
7,
5,
7,
17,
19,
27,
8,
9,
10,
10,
10,
11,
11,
10,
12,
11,
9,
10,
9,
9,
9,
9,
10,
11,
10,
10,
8,
6,
6,
5,
7,
5,
6,
5,
8,
13,
15,
19,
21,
17,
12,
8,
6,
6,
8,
12,
9,
10,
12,
14,
14,
14,
13,
11,
10,
8,
6,
6,
5,
5,
5,
6,
7,
8,
9,
6,
6,
11,
16,
13,
6,
6,
7,
10,
6,
7,
6,
7,
14,
10,
13,
15,
20,
28,
21,
7,
6,
11,
11,
9,
7,
17,
8,
8,
10,
9,
8,
8,
8,
9,
10,
11,
10,
8,
10,
7,
12,
11,
10,
9,
9,
9,
9,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
8,
7,
7,
8,
8,
7,
8,
8,
9,
11,
11,
9,
9,
8,
6,
7,
8,
9,
9,
7,
5,
5,
6,
11,
4,
14,
13,
11,
23,
17,
13,
12,
6,
9,
12,
10,
15,
11,
9,
11,
10,
10,
8,
7,
8,
8,
7,
8,
7,
7,
7,
3,
7,
9,
8,
6,
6,
7,
7,
6,
9,
7,
7,
7,
7,
9,
6,
9,
6,
9,
5,
12,
7,
11,
8,
7,
8,
7,
8,
9,
8,
9,
7,
12,
6,
10,
8,
8,
9,
9,
8,
10,
8,
8,
8,
8,
8,
8,
9,
9,
9,
8,
8,
8,
10,
7,
9,
8,
8,
11,
8,
8,
9,
9,
9,
8,
9,
9,
9,
9,
7,
10,
9,
9,
9,
9,
8,
8,
8,
8,
9,
8,
7,
8,
9,
9,
8,
7,
9,
8,
8,
8,
9,
8,
8,
8,
8,
8,
9,
8,
8,
8,
8,
8,
9,
6,
6
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
167,
167
],
[
245,
245
],
[
313,
313
]
]
},
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
7,
8,
8,
8,
8,
8,
8,
7,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
8,
8,
8,
8,
9,
9,
8,
8,
7,
8,
7,
6,
6,
6,
11,
7,
7,
9,
9,
10,
10,
17,
18,
18,
17,
11,
5,
7,
5,
7,
17,
19,
27,
8,
9,
10,
10,
10,
11,
11,
10,
12,
11,
9,
10,
9,
9,
9,
9,
10,
11,
10,
10,
8,
6,
6,
5,
7,
5,
6,
5,
8,
13,
15,
19,
21,
17,
12,
8,
6,
6,
8,
12,
9,
10,
12,
14,
14,
14,
13,
11,
10,
8,
6,
6,
5,
5,
5,
6,
7,
8,
9,
6,
6,
11,
16,
13,
6,
6,
7,
10,
6,
7,
6,
7,
14,
10,
13,
15,
20,
28,
21,
7,
6,
11,
11,
9,
7,
17,
8,
8,
10,
9,
8,
8,
8,
9,
10,
11,
10,
8,
10,
7,
12,
11,
10,
9,
9,
9,
9,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
8,
7,
7,
8,
8,
7,
8,
8,
9,
11,
11,
9,
9,
8,
6,
7,
8,
9,
9,
7,
5,
5,
6,
11,
4,
14,
13,
11,
23,
17,
13,
12,
6,
9,
12,
10,
15,
11,
9,
11,
10,
10,
8,
7,
8,
8,
7,
8,
7,
7,
7,
3,
7,
9,
8,
6,
6,
7,
7,
6,
9,
7,
7,
7,
7,
9,
6,
9,
6,
9,
5,
12,
7,
11,
8,
7,
8,
7,
8,
9,
8,
9,
7,
12,
6,
10,
8,
8,
9,
9,
8,
10,
8,
8,
8,
8,
8,
8,
9,
9,
9,
8,
8,
8,
10,
7,
9,
8,
8,
11,
8,
8,
9,
9,
9,
8,
9,
9,
9,
9,
7,
10,
9,
9,
9,
9,
8,
8,
8,
8,
9,
8,
7,
8,
9,
9,
8,
7,
9,
8,
8,
8,
9,
8,
8,
8,
8,
8,
9,
8,
8,
8,
8,
8,
9,
6,
6
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
138
],
[
141,
148
],
[
150,
151
],
[
161,
164
],
[
168,
168
],
[
188,
196
],
[
203,
206
],
[
217,
225
],
[
227,
228
],
[
232,
234
],
[
236,
239
],
[
247,
248
],
[
252,
252
],
[
254,
255
],
[
258,
260
],
[
265,
265
],
[
267,
267
],
[
275,
292
],
[
298,
301
],
[
304,
307
],
[
309,
309
],
[
317,
317
],
[
327,
337
],
[
339,
344
],
[
346,
349
],
[
351,
351
],
[
353,
353
],
[
355,
355
],
[
357,
357
],
[
359,
363
],
[
365,
365
],
[
367,
367
],
[
369,
369
],
[
371,
372
],
[
375,
375
],
[
377,
382
],
[
386,
388
],
[
390,
390
],
[
392,
393
],
[
395,
396
],
[
400,
400
],
[
405,
405
],
[
411,
414
],
[
416,
418
],
[
421,
422
],
[
424,
426
],
[
428,
432
],
[
434,
438
],
[
440,
441
]
]
}
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
4,
5,
4,
3,
4,
4,
3,
4,
3,
3,
2,
4,
3,
3,
2,
1,
1,
2,
1,
3,
1,
1,
0,
1,
3,
2,
2,
3,
4,
2,
3,
4,
4,
5,
6,
5,
3,
4,
3,
8,
4,
7,
13,
5,
7,
10,
5,
3,
3,
5,
5,
4,
4,
5,
5,
7,
6,
5,
5,
4,
5,
4,
5,
4,
4,
4,
5,
4,
4,
4,
4,
5,
5,
5,
5,
6,
5,
6,
6,
7,
9,
6,
6,
7,
6,
6,
6,
6,
7,
9,
9,
9,
10,
5,
11,
16,
12,
8,
14,
8,
9,
8,
7,
4,
4,
4,
6,
4,
7,
6,
5,
3,
5,
5,
5,
3,
8,
3,
7,
4,
5,
6,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
5,
6,
6,
6,
5,
5,
5,
5,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
3,
3,
3,
4,
3,
4,
3,
3,
3,
4,
3,
3,
4,
3,
4,
3,
4,
3,
3,
3,
4,
4,
3,
4,
4,
3,
3,
4,
4,
4,
4,
4,
4,
4,
3,
4,
5,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
2,
6,
5,
3,
4,
4,
5,
3,
5,
4,
5,
4,
4,
4,
4,
4,
4,
3,
5,
4,
5,
4,
4,
4,
4,
4,
5,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
4,
5,
4,
3,
3,
4,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
3,
3
] | {
"1. Frame Length": "The total frame length is: 503.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
4,
5,
4,
3,
4,
4,
3,
4,
3,
3,
2,
4,
3,
3,
2,
1,
1,
2,
1,
3,
1,
1,
0,
1,
3,
2,
2,
3,
4,
2,
3,
4,
4,
5,
6,
5,
3,
4,
3,
8,
4,
7,
13,
5,
7,
10,
5,
3,
3,
5,
5,
4,
4,
5,
5,
7,
6,
5,
5,
4,
5,
4,
5,
4,
4,
4,
5,
4,
4,
4,
4,
5,
5,
5,
5,
6,
5,
6,
6,
7,
9,
6,
6,
7,
6,
6,
6,
6,
7,
9,
9,
9,
10,
5,
11,
16,
12,
8,
14,
8,
9,
8,
7,
4,
4,
4,
6,
4,
7,
6,
5,
3,
5,
5,
5,
3,
8,
3,
7,
4,
5,
6,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
5,
6,
6,
6,
5,
5,
5,
5,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
3,
3,
3,
4,
3,
4,
3,
3,
3,
4,
3,
3,
4,
3,
4,
3,
4,
3,
3,
3,
4,
4,
3,
4,
4,
3,
3,
4,
4,
4,
4,
4,
4,
4,
3,
4,
5,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
2,
6,
5,
3,
4,
4,
5,
3,
5,
4,
5,
4,
4,
4,
4,
4,
4,
3,
5,
4,
5,
4,
4,
4,
4,
4,
5,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
4,
5,
4,
3,
3,
4,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
3,
3
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
228,
228
],
[
281,
281
],
[
284,
284
]
]
},
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
4,
5,
4,
3,
4,
4,
3,
4,
3,
3,
2,
4,
3,
3,
2,
1,
1,
2,
1,
3,
1,
1,
0,
1,
3,
2,
2,
3,
4,
2,
3,
4,
4,
5,
6,
5,
3,
4,
3,
8,
4,
7,
13,
5,
7,
10,
5,
3,
3,
5,
5,
4,
4,
5,
5,
7,
6,
5,
5,
4,
5,
4,
5,
4,
4,
4,
5,
4,
4,
4,
4,
5,
5,
5,
5,
6,
5,
6,
6,
7,
9,
6,
6,
7,
6,
6,
6,
6,
7,
9,
9,
9,
10,
5,
11,
16,
12,
8,
14,
8,
9,
8,
7,
4,
4,
4,
6,
4,
7,
6,
5,
3,
5,
5,
5,
3,
8,
3,
7,
4,
5,
6,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
5,
6,
6,
6,
5,
5,
5,
5,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
3,
3,
3,
4,
3,
4,
3,
3,
3,
4,
3,
3,
4,
3,
4,
3,
4,
3,
3,
3,
4,
4,
3,
4,
4,
3,
3,
4,
4,
4,
4,
4,
4,
4,
3,
4,
5,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
2,
6,
5,
3,
4,
4,
5,
3,
5,
4,
5,
4,
4,
4,
4,
4,
4,
3,
5,
4,
5,
4,
4,
4,
4,
4,
5,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
4,
5,
4,
3,
3,
4,
4,
4,
4,
4,
3,
4,
4,
4,
3,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
4,
4,
4,
4,
3,
3,
4,
4,
4,
3,
3,
3
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
6,
6
],
[
157,
157
],
[
163,
164
],
[
166,
182
],
[
184,
185
],
[
189,
189
],
[
192,
192
],
[
194,
196
],
[
198,
213
],
[
215,
216
],
[
222,
222
],
[
224,
224
],
[
233,
234
],
[
297,
297
],
[
301,
301
],
[
303,
303
],
[
346,
346
],
[
349,
351
],
[
353,
353
],
[
355,
357
],
[
359,
360
],
[
362,
362
],
[
364,
364
],
[
366,
368
],
[
371,
371
],
[
374,
375
],
[
383,
383
],
[
387,
387
],
[
404,
404
],
[
407,
407
],
[
411,
411
],
[
421,
421
],
[
436,
436
],
[
441,
441
],
[
445,
445
],
[
450,
451
],
[
457,
457
],
[
461,
461
],
[
463,
463
],
[
477,
477
],
[
480,
480
],
[
489,
489
],
[
495,
496
],
[
500,
502
]
]
}
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
10,
10,
10,
8,
5,
11,
8,
8,
8,
7,
8,
8,
8,
8,
7,
7,
8,
8,
8,
8,
7,
8,
8,
7,
8,
7,
8,
8,
7,
8,
8,
8,
7,
8,
8,
7,
7,
8,
7,
8,
8,
8,
8,
7,
8,
7,
8,
8,
8,
7,
8,
8,
7,
8,
7,
7,
8,
7,
8,
8,
7,
8,
8,
7,
8,
7,
8,
8,
8,
7,
7,
8,
8,
8,
7,
8,
7,
7,
8,
8,
7,
7,
8,
8,
8,
8,
7,
7,
8,
7,
8,
8,
8,
7,
8,
7,
8,
7,
8,
8,
8,
7,
8,
8,
7,
8,
7,
7,
8,
7,
7,
8,
7,
8,
7,
7,
8,
7,
8,
8,
8,
7,
7,
8,
8,
8,
7,
7,
8,
8,
8,
7,
8,
8,
7,
8,
8,
8,
7,
8,
8,
8,
8,
7,
8,
7,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
8,
8,
8,
7,
7,
8,
7,
7,
8,
8,
7,
8,
8,
7,
8,
7,
7,
8,
7,
7,
8,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
7,
7,
8,
7,
8,
7,
8,
8,
8,
8,
7,
7,
8,
8,
8,
8,
8,
7,
7,
7,
7,
8,
7,
7,
6,
10,
8,
7,
7,
7,
8,
7,
7,
8,
7,
8,
8,
7,
7,
7,
7,
8,
8,
7,
7,
7,
8,
7,
7,
8,
7,
7,
8,
8,
7,
7,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
7,
8,
9,
8,
8,
8,
8,
8,
8,
8,
8,
9,
9,
9,
9,
9,
9,
9,
9,
8,
9,
9,
9,
9,
8,
9,
9,
8,
8,
9,
9,
9,
10,
8,
8,
10,
8,
10,
9,
8,
8,
9,
9,
10,
9,
9,
9,
9,
9,
9,
8,
11,
7,
10,
9,
9,
9,
9,
9,
9,
10,
8,
8,
9,
8,
9,
10,
9,
9,
9,
9,
12,
9,
9,
10,
9,
9,
9,
9,
9,
9,
10,
9,
8,
9,
10,
8,
8,
13,
12,
8,
10,
8,
9,
9,
8,
9,
10,
8,
9,
11,
15,
8,
7,
9,
12,
9,
7,
7,
8,
7,
8,
7,
7,
8,
8,
7,
9,
8,
6,
6,
8,
8,
6,
10,
21,
5,
5,
6,
6,
6,
6,
5,
5,
6,
6,
6,
4,
5,
6,
8,
5,
5,
5,
4,
14,
14,
8,
10,
4,
4,
4,
4,
3,
3,
6,
5,
5,
6,
6,
7,
6,
4,
5,
5,
3,
3,
3,
5,
3,
3,
1,
6,
2,
15,
17,
36,
89,
184,
146,
104,
33,
31,
11,
24,
8,
10,
10,
6,
5,
5,
7,
15,
18,
11,
14,
9,
16,
20,
14,
30,
18,
16,
17,
14,
15,
17,
16,
16,
13,
15,
17,
17,
14,
13,
13,
15,
17,
14,
14,
14,
15,
13,
12,
15,
15,
13,
16,
15,
13,
11,
11,
10,
10,
10,
11,
9,
11,
8,
8,
9,
8,
7,
7,
6,
6,
6,
9,
5,
9,
13,
10,
14,
9,
9,
10,
9,
5,
7,
12,
3,
3,
3,
3,
8,
6,
5,
7,
5,
7,
4,
4,
8,
7,
2,
10,
7,
6,
6,
5,
3,
12,
5,
8,
8,
12,
9,
14,
11,
8,
8,
6,
10,
10,
9,
10,
12,
8,
11,
9,
10,
11,
10,
10,
8,
19,
6,
11,
10,
12,
10,
9,
10,
10,
10,
12,
11,
9,
10,
10,
11,
12,
10,
9,
11,
11,
9,
9,
12,
9,
10,
13,
7,
11,
9,
11,
9,
10,
9,
11,
10,
9,
9,
8,
11,
10,
9,
8,
9,
9,
9,
9,
8,
9,
9,
8,
9,
9,
9,
9,
9,
8,
9,
9,
8,
9,
9,
8,
8,
8,
10,
10,
9,
8,
9,
8,
9,
8,
7,
8,
10,
9,
8,
8,
9,
9,
7,
9,
10,
9,
8,
9,
9,
9,
9,
7,
7,
10,
10,
8,
8,
8,
8,
10,
9,
8,
9,
8,
9,
9,
8,
8,
9,
8,
9,
9,
9,
8,
9,
8,
9,
9,
9,
8,
8,
9,
9,
8,
8,
9,
9,
9,
8,
8,
8,
10,
9,
7,
8,
9,
9,
7,
9,
9,
8,
9,
8,
7,
8,
9,
9,
9,
9,
8,
8,
9,
8,
8,
8,
8,
9,
8,
8,
10,
8,
8,
8,
7,
11,
9,
8,
9,
8,
7,
8,
8,
9,
8,
9,
8,
8,
9,
8,
7,
8,
10,
8,
7,
9,
9,
9,
7,
7,
9,
9,
8,
7,
7,
11,
8,
8,
8,
8,
9,
9,
8,
8,
8,
9,
9,
8,
8,
8,
8,
9,
9,
8,
8,
8,
9,
8,
9,
8,
8,
8,
9,
9,
7,
8,
9,
9,
8,
8,
8,
9,
8,
8,
8,
9,
8,
8,
8,
8,
8,
8,
8,
8,
9,
8,
8,
8,
9,
8,
8,
8,
9,
8,
7,
9,
8,
8,
9,
9,
8,
8,
8,
8,
7,
8,
9,
9,
8,
8,
8,
8,
8,
9,
8,
8,
8,
9,
8,
8,
8,
9,
8,
8,
8,
8,
8,
8,
8,
9,
9,
8,
8,
9,
8,
8,
8,
8,
9,
9,
8,
8,
8,
8,
8,
9,
9,
8,
9,
8,
7,
9,
8,
9,
8,
8,
9,
8,
7,
7
] | {
"1. Frame Length": "The total frame length is: 884.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
10,
10,
10,
8,
5,
11,
8,
8,
8,
7,
8,
8,
8,
8,
7,
7,
8,
8,
8,
8,
7,
8,
8,
7,
8,
7,
8,
8,
7,
8,
8,
8,
7,
8,
8,
7,
7,
8,
7,
8,
8,
8,
8,
7,
8,
7,
8,
8,
8,
7,
8,
8,
7,
8,
7,
7,
8,
7,
8,
8,
7,
8,
8,
7,
8,
7,
8,
8,
8,
7,
7,
8,
8,
8,
7,
8,
7,
7,
8,
8,
7,
7,
8,
8,
8,
8,
7,
7,
8,
7,
8,
8,
8,
7,
8,
7,
8,
7,
8,
8,
8,
7,
8,
8,
7,
8,
7,
7,
8,
7,
7,
8,
7,
8,
7,
7,
8,
7,
8,
8,
8,
7,
7,
8,
8,
8,
7,
7,
8,
8,
8,
7,
8,
8,
7,
8,
8,
8,
7,
8,
8,
8,
8,
7,
8,
7,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
8,
8,
8,
7,
7,
8,
7,
7,
8,
8,
7,
8,
8,
7,
8,
7,
7,
8,
7,
7,
8,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
7,
7,
8,
7,
8,
7,
8,
8,
8,
8,
7,
7,
8,
8,
8,
8,
8,
7,
7,
7,
7,
8,
7,
7,
6,
10,
8,
7,
7,
7,
8,
7,
7,
8,
7,
8,
8,
7,
7,
7,
7,
8,
8,
7,
7,
7,
8,
7,
7,
8,
7,
7,
8,
8,
7,
7,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
7,
8,
9,
8,
8,
8,
8,
8,
8,
8,
8,
9,
9,
9,
9,
9,
9,
9,
9,
8,
9,
9,
9,
9,
8,
9,
9,
8,
8,
9,
9,
9,
10,
8,
8,
10,
8,
10,
9,
8,
8,
9,
9,
10,
9,
9,
9,
9,
9,
9,
8,
11,
7,
10,
9,
9,
9,
9,
9,
9,
10,
8,
8,
9,
8,
9,
10,
9,
9,
9,
9,
12,
9,
9,
10,
9,
9,
9,
9,
9,
9,
10,
9,
8,
9,
10,
8,
8,
13,
12,
8,
10,
8,
9,
9,
8,
9,
10,
8,
9,
11,
15,
8,
7,
9,
12,
9,
7,
7,
8,
7,
8,
7,
7,
8,
8,
7,
9,
8,
6,
6,
8,
8,
6,
10,
21,
5,
5,
6,
6,
6,
6,
5,
5,
6,
6,
6,
4,
5,
6,
8,
5,
5,
5,
4,
14,
14,
8,
10,
4,
4,
4,
4,
3,
3,
6,
5,
5,
6,
6,
7,
6,
4,
5,
5,
3,
3,
3,
5,
3,
3,
1,
6,
2,
15,
17,
36,
89,
184,
146,
104,
33,
31,
11,
24,
8,
10,
10,
6,
5,
5,
7,
15,
18,
11,
14,
9,
16,
20,
14,
30,
18,
16,
17,
14,
15,
17,
16,
16,
13,
15,
17,
17,
14,
13,
13,
15,
17,
14,
14,
14,
15,
13,
12,
15,
15,
13,
16,
15,
13,
11,
11,
10,
10,
10,
11,
9,
11,
8,
8,
9,
8,
7,
7,
6,
6,
6,
9,
5,
9,
13,
10,
14,
9,
9,
10,
9,
5,
7,
12,
3,
3,
3,
3,
8,
6,
5,
7,
5,
7,
4,
4,
8,
7,
2,
10,
7,
6,
6,
5,
3,
12,
5,
8,
8,
12,
9,
14,
11,
8,
8,
6,
10,
10,
9,
10,
12,
8,
11,
9,
10,
11,
10,
10,
8,
19,
6,
11,
10,
12,
10,
9,
10,
10,
10,
12,
11,
9,
10,
10,
11,
12,
10,
9,
11,
11,
9,
9,
12,
9,
10,
13,
7,
11,
9,
11,
9,
10,
9,
11,
10,
9,
9,
8,
11,
10,
9,
8,
9,
9,
9,
9,
8,
9,
9,
8,
9,
9,
9,
9,
9,
8,
9,
9,
8,
9,
9,
8,
8,
8,
10,
10,
9,
8,
9,
8,
9,
8,
7,
8,
10,
9,
8,
8,
9,
9,
7,
9,
10,
9,
8,
9,
9,
9,
9,
7,
7,
10,
10,
8,
8,
8,
8,
10,
9,
8,
9,
8,
9,
9,
8,
8,
9,
8,
9,
9,
9,
8,
9,
8,
9,
9,
9,
8,
8,
9,
9,
8,
8,
9,
9,
9,
8,
8,
8,
10,
9,
7,
8,
9,
9,
7,
9,
9,
8,
9,
8,
7,
8,
9,
9,
9,
9,
8,
8,
9,
8,
8,
8,
8,
9,
8,
8,
10,
8,
8,
8,
7,
11,
9,
8,
9,
8,
7,
8,
8,
9,
8,
9,
8,
8,
9,
8,
7,
8,
10,
8,
7,
9,
9,
9,
7,
7,
9,
9,
8,
7,
7,
11,
8,
8,
8,
8,
9,
9,
8,
8,
8,
9,
9,
8,
8,
8,
8,
9,
9,
8,
8,
8,
9,
8,
9,
8,
8,
8,
9,
9,
7,
8,
9,
9,
8,
8,
8,
9,
8,
8,
8,
9,
8,
8,
8,
8,
8,
8,
8,
8,
9,
8,
8,
8,
9,
8,
8,
8,
9,
8,
7,
9,
8,
8,
9,
9,
8,
8,
8,
8,
7,
8,
9,
9,
8,
8,
8,
8,
8,
9,
8,
8,
8,
9,
8,
8,
8,
9,
8,
8,
8,
8,
8,
8,
8,
9,
9,
8,
8,
9,
8,
8,
8,
8,
9,
9,
8,
8,
8,
8,
8,
9,
9,
8,
9,
8,
7,
9,
8,
9,
8,
8,
9,
8,
7,
7
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
439,
439
]
]
},
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
10,
10,
10,
8,
5,
11,
8,
8,
8,
7,
8,
8,
8,
8,
7,
7,
8,
8,
8,
8,
7,
8,
8,
7,
8,
7,
8,
8,
7,
8,
8,
8,
7,
8,
8,
7,
7,
8,
7,
8,
8,
8,
8,
7,
8,
7,
8,
8,
8,
7,
8,
8,
7,
8,
7,
7,
8,
7,
8,
8,
7,
8,
8,
7,
8,
7,
8,
8,
8,
7,
7,
8,
8,
8,
7,
8,
7,
7,
8,
8,
7,
7,
8,
8,
8,
8,
7,
7,
8,
7,
8,
8,
8,
7,
8,
7,
8,
7,
8,
8,
8,
7,
8,
8,
7,
8,
7,
7,
8,
7,
7,
8,
7,
8,
7,
7,
8,
7,
8,
8,
8,
7,
7,
8,
8,
8,
7,
7,
8,
8,
8,
7,
8,
8,
7,
8,
8,
8,
7,
8,
8,
8,
8,
7,
8,
7,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
8,
8,
8,
7,
7,
8,
7,
7,
8,
8,
7,
8,
8,
7,
8,
7,
7,
8,
7,
7,
8,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
7,
7,
8,
7,
8,
7,
8,
8,
8,
8,
7,
7,
8,
8,
8,
8,
8,
7,
7,
7,
7,
8,
7,
7,
6,
10,
8,
7,
7,
7,
8,
7,
7,
8,
7,
8,
8,
7,
7,
7,
7,
8,
8,
7,
7,
7,
8,
7,
7,
8,
7,
7,
8,
8,
7,
7,
8,
8,
7,
8,
8,
8,
8,
7,
8,
8,
7,
8,
9,
8,
8,
8,
8,
8,
8,
8,
8,
9,
9,
9,
9,
9,
9,
9,
9,
8,
9,
9,
9,
9,
8,
9,
9,
8,
8,
9,
9,
9,
10,
8,
8,
10,
8,
10,
9,
8,
8,
9,
9,
10,
9,
9,
9,
9,
9,
9,
8,
11,
7,
10,
9,
9,
9,
9,
9,
9,
10,
8,
8,
9,
8,
9,
10,
9,
9,
9,
9,
12,
9,
9,
10,
9,
9,
9,
9,
9,
9,
10,
9,
8,
9,
10,
8,
8,
13,
12,
8,
10,
8,
9,
9,
8,
9,
10,
8,
9,
11,
15,
8,
7,
9,
12,
9,
7,
7,
8,
7,
8,
7,
7,
8,
8,
7,
9,
8,
6,
6,
8,
8,
6,
10,
21,
5,
5,
6,
6,
6,
6,
5,
5,
6,
6,
6,
4,
5,
6,
8,
5,
5,
5,
4,
14,
14,
8,
10,
4,
4,
4,
4,
3,
3,
6,
5,
5,
6,
6,
7,
6,
4,
5,
5,
3,
3,
3,
5,
3,
3,
1,
6,
2,
15,
17,
36,
89,
184,
146,
104,
33,
31,
11,
24,
8,
10,
10,
6,
5,
5,
7,
15,
18,
11,
14,
9,
16,
20,
14,
30,
18,
16,
17,
14,
15,
17,
16,
16,
13,
15,
17,
17,
14,
13,
13,
15,
17,
14,
14,
14,
15,
13,
12,
15,
15,
13,
16,
15,
13,
11,
11,
10,
10,
10,
11,
9,
11,
8,
8,
9,
8,
7,
7,
6,
6,
6,
9,
5,
9,
13,
10,
14,
9,
9,
10,
9,
5,
7,
12,
3,
3,
3,
3,
8,
6,
5,
7,
5,
7,
4,
4,
8,
7,
2,
10,
7,
6,
6,
5,
3,
12,
5,
8,
8,
12,
9,
14,
11,
8,
8,
6,
10,
10,
9,
10,
12,
8,
11,
9,
10,
11,
10,
10,
8,
19,
6,
11,
10,
12,
10,
9,
10,
10,
10,
12,
11,
9,
10,
10,
11,
12,
10,
9,
11,
11,
9,
9,
12,
9,
10,
13,
7,
11,
9,
11,
9,
10,
9,
11,
10,
9,
9,
8,
11,
10,
9,
8,
9,
9,
9,
9,
8,
9,
9,
8,
9,
9,
9,
9,
9,
8,
9,
9,
8,
9,
9,
8,
8,
8,
10,
10,
9,
8,
9,
8,
9,
8,
7,
8,
10,
9,
8,
8,
9,
9,
7,
9,
10,
9,
8,
9,
9,
9,
9,
7,
7,
10,
10,
8,
8,
8,
8,
10,
9,
8,
9,
8,
9,
9,
8,
8,
9,
8,
9,
9,
9,
8,
9,
8,
9,
9,
9,
8,
8,
9,
9,
8,
8,
9,
9,
9,
8,
8,
8,
10,
9,
7,
8,
9,
9,
7,
9,
9,
8,
9,
8,
7,
8,
9,
9,
9,
9,
8,
8,
9,
8,
8,
8,
8,
9,
8,
8,
10,
8,
8,
8,
7,
11,
9,
8,
9,
8,
7,
8,
8,
9,
8,
9,
8,
8,
9,
8,
7,
8,
10,
8,
7,
9,
9,
9,
7,
7,
9,
9,
8,
7,
7,
11,
8,
8,
8,
8,
9,
9,
8,
8,
8,
9,
9,
8,
8,
8,
8,
9,
9,
8,
8,
8,
9,
8,
9,
8,
8,
8,
9,
9,
7,
8,
9,
9,
8,
8,
8,
9,
8,
8,
8,
9,
8,
8,
8,
8,
8,
8,
8,
8,
9,
8,
8,
8,
9,
8,
8,
8,
9,
8,
7,
9,
8,
8,
9,
9,
8,
8,
8,
8,
7,
8,
9,
9,
8,
8,
8,
8,
8,
9,
8,
8,
8,
9,
8,
8,
8,
9,
8,
8,
8,
8,
8,
8,
8,
9,
9,
8,
8,
9,
8,
8,
8,
8,
9,
9,
8,
8,
8,
8,
8,
9,
9,
8,
9,
8,
7,
9,
8,
9,
8,
8,
9,
8,
7,
7
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
437
],
[
442,
883
]
]
}
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
6,
6,
5,
6,
6,
6,
6,
6,
6,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
6,
5,
6,
6,
6,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
8,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
6,
6,
5,
6,
6,
6,
6
] | {
"1. Frame Length": "The total frame length is: 423.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
6,
6,
5,
6,
6,
6,
6,
6,
6,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
6,
5,
6,
6,
6,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
8,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
6,
6,
5,
6,
6,
6,
6
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
95,
95
],
[
103,
105
],
[
111,
117
],
[
124,
133
],
[
135,
168
],
[
170,
240
],
[
242,
254
],
[
303,
303
],
[
325,
325
],
[
331,
331
]
]
},
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
6,
6,
5,
6,
6,
6,
6,
6,
6,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
6,
5,
6,
6,
6,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
8,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
6,
6,
5,
6,
6,
6,
6
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
2,
2
],
[
9,
10
],
[
59,
59
],
[
61,
61
],
[
65,
65
],
[
415,
415
],
[
418,
418
]
]
}
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
8,
7,
6,
6,
6,
7,
7,
7,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
6,
6,
7,
7,
11,
7,
6,
7,
7,
7,
7,
6,
6,
7,
7,
7,
7,
7,
7,
7,
8,
8,
8,
8,
7,
7,
7,
7,
7,
8,
7,
8,
8,
7,
7,
7,
7,
7,
7,
6,
8,
7,
7,
7,
7,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
7,
7,
6,
6,
7,
6,
8,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
7,
7,
7,
8,
6,
6,
7,
7,
7,
7,
8,
8,
7,
7,
7,
7,
7,
7,
8,
8,
9,
9,
10,
8,
5,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
7,
7,
7,
7,
7,
6,
6,
6,
7,
7,
7,
7,
7,
7,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
8,
8,
8,
8,
7,
7,
7,
7,
7,
8,
8,
8,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7
] | {
"1. Frame Length": "The total frame length is: 469.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
8,
7,
6,
6,
6,
7,
7,
7,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
6,
6,
7,
7,
11,
7,
6,
7,
7,
7,
7,
6,
6,
7,
7,
7,
7,
7,
7,
7,
8,
8,
8,
8,
7,
7,
7,
7,
7,
8,
7,
8,
8,
7,
7,
7,
7,
7,
7,
6,
8,
7,
7,
7,
7,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
7,
7,
6,
6,
7,
6,
8,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
7,
7,
7,
8,
6,
6,
7,
7,
7,
7,
8,
8,
7,
7,
7,
7,
7,
7,
8,
8,
9,
9,
10,
8,
5,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
7,
7,
7,
7,
7,
6,
6,
6,
7,
7,
7,
7,
7,
7,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
8,
8,
8,
8,
7,
7,
7,
7,
7,
8,
8,
8,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
89,
89
],
[
194,
196
]
]
},
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
8,
7,
6,
6,
6,
7,
7,
7,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
6,
6,
7,
7,
11,
7,
6,
7,
7,
7,
7,
6,
6,
7,
7,
7,
7,
7,
7,
7,
8,
8,
8,
8,
7,
7,
7,
7,
7,
8,
7,
8,
8,
7,
7,
7,
7,
7,
7,
6,
8,
7,
7,
7,
7,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
7,
7,
6,
6,
7,
6,
8,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
7,
7,
7,
8,
6,
6,
7,
7,
7,
7,
8,
8,
7,
7,
7,
7,
7,
7,
8,
8,
9,
9,
10,
8,
5,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
8,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
7,
7,
7,
7,
7,
6,
6,
6,
7,
7,
7,
7,
7,
7,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
8,
8,
8,
8,
7,
7,
7,
7,
7,
8,
8,
8,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
7,
7,
7,
7,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
41,
43
],
[
54,
54
],
[
58,
60
],
[
65,
81
],
[
85,
86
],
[
91,
91
],
[
96,
97
],
[
124,
124
],
[
130,
131
],
[
142,
143
],
[
146,
147
],
[
149,
149
],
[
151,
168
],
[
170,
173
],
[
178,
179
],
[
198,
198
],
[
225,
225
],
[
274,
276
],
[
318,
320
],
[
326,
328
],
[
335,
335
],
[
337,
357
],
[
389,
389
],
[
410,
410
],
[
416,
417
],
[
434,
435
],
[
440,
440
]
]
}
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
5,
5,
4,
5,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
5,
5,
5,
4,
4,
5,
4,
4,
5,
4,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
4,
4,
4,
4,
5,
4,
5,
5,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
6,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
14,
13,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
6,
6,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
10,
12,
10,
8,
6,
7,
10,
12,
12,
10,
16,
6,
7,
8,
9,
9,
8,
7,
6,
6,
5,
5,
7,
4,
5,
5,
5,
5,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5
] | {
"1. Frame Length": "The total frame length is: 586.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
5,
5,
4,
5,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
5,
5,
5,
4,
4,
5,
4,
4,
5,
4,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
4,
4,
4,
4,
5,
4,
5,
5,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
6,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
14,
13,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
6,
6,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
10,
12,
10,
8,
6,
7,
10,
12,
12,
10,
16,
6,
7,
8,
9,
9,
8,
7,
6,
6,
5,
5,
7,
4,
5,
5,
5,
5,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
231,
232
],
[
303,
303
]
]
},
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
5,
5,
4,
5,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
5,
5,
5,
4,
4,
5,
4,
4,
5,
4,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
4,
4,
4,
4,
5,
4,
5,
5,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
6,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
14,
13,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
6,
6,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
10,
12,
10,
8,
6,
7,
10,
12,
12,
10,
16,
6,
7,
8,
9,
9,
8,
7,
6,
6,
5,
5,
7,
4,
5,
5,
5,
5,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
230
],
[
233,
244
],
[
251,
255
],
[
262,
292
],
[
297,
297
],
[
304,
304
],
[
311,
314
],
[
316,
585
]
]
}
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
6,
6,
4,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
5,
4,
5,
5,
4,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
5,
5,
5,
5,
5,
5,
5,
4,
5,
5,
4,
5,
5,
4,
5,
4,
5,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
6,
5,
6,
5,
6,
5,
6,
5,
5,
6,
5,
5,
6,
5,
5,
5,
5,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
3,
3,
3,
2,
5,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3
] | {
"1. Frame Length": "The total frame length is: 399.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
6,
6,
4,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
5,
4,
5,
5,
4,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
5,
5,
5,
5,
5,
5,
5,
4,
5,
5,
4,
5,
5,
4,
5,
4,
5,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
6,
5,
6,
5,
6,
5,
6,
5,
5,
6,
5,
5,
6,
5,
5,
5,
5,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
3,
3,
3,
2,
5,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
0,
1
],
[
3,
3
],
[
39,
47
],
[
49,
61
],
[
68,
68
],
[
70,
71
],
[
73,
73
],
[
101,
137
],
[
139,
145
],
[
147,
148
],
[
150,
151
],
[
153,
153
],
[
155,
155
],
[
157,
312
],
[
314,
314
],
[
380,
380
]
]
},
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
6,
6,
4,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
5,
4,
5,
5,
4,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
5,
5,
5,
5,
5,
5,
5,
4,
5,
5,
4,
5,
5,
4,
5,
4,
5,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
6,
5,
6,
5,
6,
5,
6,
5,
5,
6,
5,
5,
6,
5,
5,
5,
5,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
5,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
3,
4,
3,
3,
3,
2,
5,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
339,
344
],
[
353,
353
],
[
379,
379
],
[
387,
395
]
]
}
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
15,
28,
4,
3,
4,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
6,
18,
4,
4,
5,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
4,
3,
9,
25,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
5,
5,
5,
5,
5,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
11,
20,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
9,
21,
6,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
14,
5,
4,
5,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
6,
17,
8,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
6,
4,
13,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
9,
22,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
14,
5,
4,
6,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
6,
4,
5,
5
] | {
"1. Frame Length": "The total frame length is: 401.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
15,
28,
4,
3,
4,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
6,
18,
4,
4,
5,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
4,
3,
9,
25,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
5,
5,
5,
5,
5,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
11,
20,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
9,
21,
6,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
14,
5,
4,
5,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
6,
17,
8,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
6,
4,
13,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
9,
22,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
14,
5,
4,
6,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
6,
4,
5,
5
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
23,
23
],
[
111,
111
]
]
},
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
15,
28,
4,
3,
4,
3,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
6,
18,
4,
4,
5,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
4,
3,
9,
25,
4,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
5,
5,
5,
5,
5,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
11,
20,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
9,
21,
6,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
14,
5,
4,
5,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
6,
17,
8,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
6,
4,
13,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
9,
22,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
14,
5,
4,
6,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
6,
4,
5,
5
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
21
],
[
24,
67
],
[
69,
109
],
[
112,
145
],
[
148,
171
],
[
174,
217
],
[
219,
255
],
[
258,
295
],
[
297,
323
],
[
326,
368
],
[
370,
400
]
]
}
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
2,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
4,
4,
2,
2,
2,
2,
2,
2,
6,
3,
4,
2,
5,
5,
6,
5,
9,
7,
7,
4,
3,
3,
2,
2,
2,
3,
3,
3,
2,
12,
8,
2,
8,
11,
4,
21,
6,
6,
6,
4,
5,
3,
2,
2,
2,
2,
3,
5,
3,
3,
4,
4,
2,
2,
2,
3,
3,
6,
4,
3,
2,
4,
6,
7,
5,
3,
11,
13,
7,
17,
8,
10,
6,
4,
5,
4,
3,
4,
4,
4,
4,
3,
3,
3,
4,
3,
5,
11,
2,
13,
6,
3,
7,
2,
2,
2,
3,
5,
3,
2,
2,
7,
5,
7,
6,
4,
2,
4,
4,
7,
2,
3,
11,
12,
31,
10,
4,
7,
8,
4,
15,
10,
6,
5,
8,
8,
4,
5,
4,
3,
3,
3,
3,
5,
5,
5,
9,
11,
4,
63,
13,
16,
27,
8,
18,
12,
4,
4,
5,
2,
3,
4,
3,
11,
5,
7,
2,
4,
2,
4,
5,
2,
4,
2,
2,
3,
3,
2,
3,
2,
3,
2,
2,
2,
2,
4,
2,
3,
2,
3,
3,
3,
3,
3,
3,
3,
2,
4,
2,
3,
3,
3,
2,
2,
3,
2,
2,
2,
2,
3,
2,
2,
3,
2,
3,
3,
3,
2,
3,
2,
2,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
2,
2,
2,
3,
2,
2
] | {
"1. Frame Length": "The total frame length is: 338.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
2,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
4,
4,
2,
2,
2,
2,
2,
2,
6,
3,
4,
2,
5,
5,
6,
5,
9,
7,
7,
4,
3,
3,
2,
2,
2,
3,
3,
3,
2,
12,
8,
2,
8,
11,
4,
21,
6,
6,
6,
4,
5,
3,
2,
2,
2,
2,
3,
5,
3,
3,
4,
4,
2,
2,
2,
3,
3,
6,
4,
3,
2,
4,
6,
7,
5,
3,
11,
13,
7,
17,
8,
10,
6,
4,
5,
4,
3,
4,
4,
4,
4,
3,
3,
3,
4,
3,
5,
11,
2,
13,
6,
3,
7,
2,
2,
2,
3,
5,
3,
2,
2,
7,
5,
7,
6,
4,
2,
4,
4,
7,
2,
3,
11,
12,
31,
10,
4,
7,
8,
4,
15,
10,
6,
5,
8,
8,
4,
5,
4,
3,
3,
3,
3,
5,
5,
5,
9,
11,
4,
63,
13,
16,
27,
8,
18,
12,
4,
4,
5,
2,
3,
4,
3,
11,
5,
7,
2,
4,
2,
4,
5,
2,
4,
2,
2,
3,
3,
2,
3,
2,
3,
2,
2,
2,
2,
4,
2,
3,
2,
3,
3,
3,
3,
3,
3,
3,
2,
4,
2,
3,
3,
3,
2,
2,
3,
2,
2,
2,
2,
3,
2,
2,
3,
2,
3,
3,
3,
2,
3,
2,
2,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
2,
2,
2,
3,
2,
2
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
244,
244
]
]
},
"3. Local Minima": null
} |
Torque represents the torque value on the limbs (both arms, both legs). Near the maximum value, the torque value on the body is higher (more movement) indicating that the body is actively performing an action. Near the minimum value, the torque value on the body is lower (less movement).
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
2,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
4,
4,
2,
2,
2,
2,
2,
2,
6,
3,
4,
2,
5,
5,
6,
5,
9,
7,
7,
4,
3,
3,
2,
2,
2,
3,
3,
3,
2,
12,
8,
2,
8,
11,
4,
21,
6,
6,
6,
4,
5,
3,
2,
2,
2,
2,
3,
5,
3,
3,
4,
4,
2,
2,
2,
3,
3,
6,
4,
3,
2,
4,
6,
7,
5,
3,
11,
13,
7,
17,
8,
10,
6,
4,
5,
4,
3,
4,
4,
4,
4,
3,
3,
3,
4,
3,
5,
11,
2,
13,
6,
3,
7,
2,
2,
2,
3,
5,
3,
2,
2,
7,
5,
7,
6,
4,
2,
4,
4,
7,
2,
3,
11,
12,
31,
10,
4,
7,
8,
4,
15,
10,
6,
5,
8,
8,
4,
5,
4,
3,
3,
3,
3,
5,
5,
5,
9,
11,
4,
63,
13,
16,
27,
8,
18,
12,
4,
4,
5,
2,
3,
4,
3,
11,
5,
7,
2,
4,
2,
4,
5,
2,
4,
2,
2,
3,
3,
2,
3,
2,
3,
2,
2,
2,
2,
4,
2,
3,
2,
3,
3,
3,
3,
3,
3,
3,
2,
4,
2,
3,
3,
3,
2,
2,
3,
2,
2,
2,
2,
3,
2,
2,
3,
2,
3,
3,
3,
2,
3,
2,
2,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
2,
2,
2,
3,
2,
2
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
139
],
[
141,
173
],
[
175,
218
],
[
220,
224
],
[
226,
243
],
[
245,
245
],
[
248,
248
],
[
250,
337
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
5,
5,
4,
5,
6,
5,
5,
6,
6,
7,
8,
7,
6,
7,
8,
7,
7,
8,
8,
8,
7,
8,
8,
7,
7,
7,
9,
8,
8,
9,
10,
10,
10,
10,
9,
12,
12,
12,
13,
16,
15,
13,
13,
14,
14,
13,
14,
16,
16,
15,
15,
16,
15,
14,
14,
14,
14,
16,
16,
15,
14,
16,
19,
16,
16,
15,
17,
18,
17,
15,
15,
15,
14,
11,
11,
9,
8,
6,
6,
5,
5,
5,
5,
6,
8,
10,
11,
12,
12,
11,
13,
13,
12,
12,
11,
11,
10,
12,
12,
13,
13,
14,
15,
16,
19,
20,
19,
20,
20,
20,
20,
20,
19,
18,
17,
17,
18,
17,
17,
17,
18,
19,
21,
21,
22,
23,
22,
23,
25,
25,
25,
27,
28,
31,
29,
27,
24,
31,
31,
23,
26,
26,
26,
27,
27,
27,
28,
26,
28,
28,
31,
31,
33,
33,
35,
33,
34,
31,
29,
29,
28,
28,
30,
30,
25,
25,
28,
26,
25,
24,
24,
23,
23,
20,
26,
30,
35,
38,
40,
41,
44,
47,
49,
50,
53,
56,
57,
52,
50,
48,
46,
51,
39,
45,
37,
36,
33,
31,
31,
30,
31,
25,
26,
25,
24,
25,
24,
24,
31,
20,
19,
22,
20,
19,
17,
26,
17,
22,
19,
18,
14,
17,
19,
21,
23,
26,
28,
29,
32,
35,
38,
39,
39,
43,
38,
41,
42,
45,
48,
51,
57,
50,
46,
49,
55,
47,
46,
33,
32,
31,
26,
26,
23,
25,
29,
26,
25,
28,
27,
28,
31,
37,
39,
38,
41,
41,
36,
41,
46,
40,
40,
41,
37,
36,
36,
33,
33,
31,
29,
29,
30,
32,
33,
28,
31,
32,
30,
26,
33,
32,
35,
32,
31,
31,
28,
20,
26,
30,
28,
30,
24,
31,
33,
37,
41,
42,
45,
46,
48,
51,
55,
58,
52,
50,
48,
51,
50,
52,
48,
42,
38,
34,
31,
29,
27,
26,
30,
27,
26,
28,
22,
28,
25,
26,
55,
21,
25,
59,
23,
17,
18,
20,
19,
20,
21,
21,
24,
20,
26,
27,
27,
32,
36,
34,
39,
39,
44,
45,
40,
47,
48,
50,
51,
40,
42,
48,
44,
44,
41,
24,
33,
30,
26,
21,
26,
21,
19,
20,
24,
20,
23,
23,
22,
21,
28,
28,
28,
25,
33,
29,
26,
31,
28,
27,
33,
25,
26,
28,
22,
28,
27,
24,
23,
26,
25,
28,
28,
24,
24,
26,
23,
22,
22,
17,
30,
20,
18,
22,
18,
20,
15,
24,
13,
24,
26,
19,
21,
21,
29,
15,
23,
15,
19,
12,
12,
10,
15,
12,
15,
21,
25,
34,
26,
38,
40,
40,
42,
38,
38,
36,
34,
32,
34,
30,
28,
27,
28,
28,
23,
27,
24,
26,
27,
21,
21,
21,
58,
14,
11,
19,
12,
8,
14,
14,
12,
16,
14,
9,
6,
3,
8,
10,
12,
12,
15,
13,
20,
19,
27,
24,
24,
30,
35,
34,
35,
39,
39,
38,
39,
38,
32,
36,
31,
43,
49,
55,
40,
45,
49,
47,
44,
20,
16,
11,
12,
13,
9,
10,
11,
8,
10,
6,
5,
3,
5
] | {
"1. Frame Length": "The total frame length is: 525.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
5,
5,
4,
5,
6,
5,
5,
6,
6,
7,
8,
7,
6,
7,
8,
7,
7,
8,
8,
8,
7,
8,
8,
7,
7,
7,
9,
8,
8,
9,
10,
10,
10,
10,
9,
12,
12,
12,
13,
16,
15,
13,
13,
14,
14,
13,
14,
16,
16,
15,
15,
16,
15,
14,
14,
14,
14,
16,
16,
15,
14,
16,
19,
16,
16,
15,
17,
18,
17,
15,
15,
15,
14,
11,
11,
9,
8,
6,
6,
5,
5,
5,
5,
6,
8,
10,
11,
12,
12,
11,
13,
13,
12,
12,
11,
11,
10,
12,
12,
13,
13,
14,
15,
16,
19,
20,
19,
20,
20,
20,
20,
20,
19,
18,
17,
17,
18,
17,
17,
17,
18,
19,
21,
21,
22,
23,
22,
23,
25,
25,
25,
27,
28,
31,
29,
27,
24,
31,
31,
23,
26,
26,
26,
27,
27,
27,
28,
26,
28,
28,
31,
31,
33,
33,
35,
33,
34,
31,
29,
29,
28,
28,
30,
30,
25,
25,
28,
26,
25,
24,
24,
23,
23,
20,
26,
30,
35,
38,
40,
41,
44,
47,
49,
50,
53,
56,
57,
52,
50,
48,
46,
51,
39,
45,
37,
36,
33,
31,
31,
30,
31,
25,
26,
25,
24,
25,
24,
24,
31,
20,
19,
22,
20,
19,
17,
26,
17,
22,
19,
18,
14,
17,
19,
21,
23,
26,
28,
29,
32,
35,
38,
39,
39,
43,
38,
41,
42,
45,
48,
51,
57,
50,
46,
49,
55,
47,
46,
33,
32,
31,
26,
26,
23,
25,
29,
26,
25,
28,
27,
28,
31,
37,
39,
38,
41,
41,
36,
41,
46,
40,
40,
41,
37,
36,
36,
33,
33,
31,
29,
29,
30,
32,
33,
28,
31,
32,
30,
26,
33,
32,
35,
32,
31,
31,
28,
20,
26,
30,
28,
30,
24,
31,
33,
37,
41,
42,
45,
46,
48,
51,
55,
58,
52,
50,
48,
51,
50,
52,
48,
42,
38,
34,
31,
29,
27,
26,
30,
27,
26,
28,
22,
28,
25,
26,
55,
21,
25,
59,
23,
17,
18,
20,
19,
20,
21,
21,
24,
20,
26,
27,
27,
32,
36,
34,
39,
39,
44,
45,
40,
47,
48,
50,
51,
40,
42,
48,
44,
44,
41,
24,
33,
30,
26,
21,
26,
21,
19,
20,
24,
20,
23,
23,
22,
21,
28,
28,
28,
25,
33,
29,
26,
31,
28,
27,
33,
25,
26,
28,
22,
28,
27,
24,
23,
26,
25,
28,
28,
24,
24,
26,
23,
22,
22,
17,
30,
20,
18,
22,
18,
20,
15,
24,
13,
24,
26,
19,
21,
21,
29,
15,
23,
15,
19,
12,
12,
10,
15,
12,
15,
21,
25,
34,
26,
38,
40,
40,
42,
38,
38,
36,
34,
32,
34,
30,
28,
27,
28,
28,
23,
27,
24,
26,
27,
21,
21,
21,
58,
14,
11,
19,
12,
8,
14,
14,
12,
16,
14,
9,
6,
3,
8,
10,
12,
12,
15,
13,
20,
19,
27,
24,
24,
30,
35,
34,
35,
39,
39,
38,
39,
38,
32,
36,
31,
43,
49,
55,
40,
45,
49,
47,
44,
20,
16,
11,
12,
13,
9,
10,
11,
8,
10,
6,
5,
3,
5
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
182,
189
],
[
191,
191
],
[
238,
241
],
[
243,
244
],
[
308,
318
],
[
334,
334
],
[
337,
337
],
[
360,
362
],
[
365,
365
],
[
466,
466
],
[
504,
505
],
[
508,
508
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
5,
5,
4,
5,
6,
5,
5,
6,
6,
7,
8,
7,
6,
7,
8,
7,
7,
8,
8,
8,
7,
8,
8,
7,
7,
7,
9,
8,
8,
9,
10,
10,
10,
10,
9,
12,
12,
12,
13,
16,
15,
13,
13,
14,
14,
13,
14,
16,
16,
15,
15,
16,
15,
14,
14,
14,
14,
16,
16,
15,
14,
16,
19,
16,
16,
15,
17,
18,
17,
15,
15,
15,
14,
11,
11,
9,
8,
6,
6,
5,
5,
5,
5,
6,
8,
10,
11,
12,
12,
11,
13,
13,
12,
12,
11,
11,
10,
12,
12,
13,
13,
14,
15,
16,
19,
20,
19,
20,
20,
20,
20,
20,
19,
18,
17,
17,
18,
17,
17,
17,
18,
19,
21,
21,
22,
23,
22,
23,
25,
25,
25,
27,
28,
31,
29,
27,
24,
31,
31,
23,
26,
26,
26,
27,
27,
27,
28,
26,
28,
28,
31,
31,
33,
33,
35,
33,
34,
31,
29,
29,
28,
28,
30,
30,
25,
25,
28,
26,
25,
24,
24,
23,
23,
20,
26,
30,
35,
38,
40,
41,
44,
47,
49,
50,
53,
56,
57,
52,
50,
48,
46,
51,
39,
45,
37,
36,
33,
31,
31,
30,
31,
25,
26,
25,
24,
25,
24,
24,
31,
20,
19,
22,
20,
19,
17,
26,
17,
22,
19,
18,
14,
17,
19,
21,
23,
26,
28,
29,
32,
35,
38,
39,
39,
43,
38,
41,
42,
45,
48,
51,
57,
50,
46,
49,
55,
47,
46,
33,
32,
31,
26,
26,
23,
25,
29,
26,
25,
28,
27,
28,
31,
37,
39,
38,
41,
41,
36,
41,
46,
40,
40,
41,
37,
36,
36,
33,
33,
31,
29,
29,
30,
32,
33,
28,
31,
32,
30,
26,
33,
32,
35,
32,
31,
31,
28,
20,
26,
30,
28,
30,
24,
31,
33,
37,
41,
42,
45,
46,
48,
51,
55,
58,
52,
50,
48,
51,
50,
52,
48,
42,
38,
34,
31,
29,
27,
26,
30,
27,
26,
28,
22,
28,
25,
26,
55,
21,
25,
59,
23,
17,
18,
20,
19,
20,
21,
21,
24,
20,
26,
27,
27,
32,
36,
34,
39,
39,
44,
45,
40,
47,
48,
50,
51,
40,
42,
48,
44,
44,
41,
24,
33,
30,
26,
21,
26,
21,
19,
20,
24,
20,
23,
23,
22,
21,
28,
28,
28,
25,
33,
29,
26,
31,
28,
27,
33,
25,
26,
28,
22,
28,
27,
24,
23,
26,
25,
28,
28,
24,
24,
26,
23,
22,
22,
17,
30,
20,
18,
22,
18,
20,
15,
24,
13,
24,
26,
19,
21,
21,
29,
15,
23,
15,
19,
12,
12,
10,
15,
12,
15,
21,
25,
34,
26,
38,
40,
40,
42,
38,
38,
36,
34,
32,
34,
30,
28,
27,
28,
28,
23,
27,
24,
26,
27,
21,
21,
21,
58,
14,
11,
19,
12,
8,
14,
14,
12,
16,
14,
9,
6,
3,
8,
10,
12,
12,
15,
13,
20,
19,
27,
24,
24,
30,
35,
34,
35,
39,
39,
38,
39,
38,
32,
36,
31,
43,
49,
55,
40,
45,
49,
47,
44,
20,
16,
11,
12,
13,
9,
10,
11,
8,
10,
6,
5,
3,
5
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
38
],
[
41,
46
],
[
53,
56
],
[
60,
60
],
[
72,
101
],
[
220,
220
],
[
422,
422
],
[
433,
435
],
[
437,
437
],
[
467,
468
],
[
470,
474
],
[
476,
483
],
[
485,
485
],
[
513,
524
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
14,
14,
16,
14,
15,
14,
14,
22,
14,
16,
19,
16,
21,
18,
17,
21,
18,
20,
21,
23,
22,
19,
27,
21,
25,
23,
21,
26,
24,
31,
23,
24,
25,
25,
29,
21,
27,
21,
25,
24,
21,
28,
19,
22,
27,
19,
24,
24,
18,
24,
25,
21,
22,
21,
23,
20,
22,
24,
22,
23,
22,
23,
23,
23,
23,
24,
20,
20,
29,
24,
24,
23,
24,
24,
22,
24,
25,
26,
25,
23,
25,
28,
27,
24,
27,
27,
27,
27,
29,
29,
29,
32,
31,
34,
29,
33,
30,
33,
30,
31,
29,
30,
27,
32,
28,
27,
29,
31,
28,
27,
27,
28,
26,
27,
28,
26,
25,
25,
27,
27,
26,
25,
23,
28,
26,
25,
25,
24,
26,
25,
26,
25,
24,
26,
26,
23,
25,
25,
25,
25,
26,
26,
27,
26,
25,
27,
28,
28,
28,
27,
28,
29,
29,
31,
31,
30,
29,
29,
31,
32,
31,
30,
31,
31,
30,
30,
29,
29,
29,
29,
28,
28,
28,
28,
28,
26,
27,
27,
27,
27,
27,
26,
26,
27,
27,
25,
26,
26,
27,
26,
26,
27,
26,
27,
26,
25,
26,
26,
28,
27,
27,
26,
26,
26,
28,
28,
28,
28,
27,
29,
29,
30,
30,
30,
30,
32,
33,
33,
34,
34,
34,
34,
34,
33,
32,
33,
32,
33,
33,
31,
31,
31,
30,
31,
30,
28,
29,
28,
29,
28,
28,
27,
28,
27,
27,
27,
27,
27,
26,
28,
27,
27,
26,
26,
26,
28,
26,
26,
26,
26,
26,
27,
28,
27,
27,
28,
29,
27,
27,
31,
29,
28,
31,
30,
29,
30,
31,
31,
30,
35,
31,
33,
31,
33,
34,
35,
32,
31,
31,
31,
30,
31,
30,
30,
30,
28,
27,
29,
30,
27,
29,
30,
23,
29,
26,
28,
26,
25,
24,
26,
26,
26,
26,
25,
25,
27,
27,
27,
27,
27,
26,
29,
27,
27,
28,
30,
29,
27,
28,
28,
28,
28,
29,
29,
29,
29,
30,
30,
30,
29,
32,
31,
33,
32,
32,
29,
33,
31,
30,
29,
29,
29,
26,
26,
30,
28,
25,
27,
27,
22,
28,
25,
28,
26,
24,
24,
23,
24,
23,
28,
23,
24,
25,
22,
24,
24,
25,
24,
21,
25,
25,
25,
24,
24,
23,
26,
23,
21,
29,
24,
28,
19,
30,
24,
34,
25
] | {
"1. Frame Length": "The total frame length is: 396.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
14,
14,
16,
14,
15,
14,
14,
22,
14,
16,
19,
16,
21,
18,
17,
21,
18,
20,
21,
23,
22,
19,
27,
21,
25,
23,
21,
26,
24,
31,
23,
24,
25,
25,
29,
21,
27,
21,
25,
24,
21,
28,
19,
22,
27,
19,
24,
24,
18,
24,
25,
21,
22,
21,
23,
20,
22,
24,
22,
23,
22,
23,
23,
23,
23,
24,
20,
20,
29,
24,
24,
23,
24,
24,
22,
24,
25,
26,
25,
23,
25,
28,
27,
24,
27,
27,
27,
27,
29,
29,
29,
32,
31,
34,
29,
33,
30,
33,
30,
31,
29,
30,
27,
32,
28,
27,
29,
31,
28,
27,
27,
28,
26,
27,
28,
26,
25,
25,
27,
27,
26,
25,
23,
28,
26,
25,
25,
24,
26,
25,
26,
25,
24,
26,
26,
23,
25,
25,
25,
25,
26,
26,
27,
26,
25,
27,
28,
28,
28,
27,
28,
29,
29,
31,
31,
30,
29,
29,
31,
32,
31,
30,
31,
31,
30,
30,
29,
29,
29,
29,
28,
28,
28,
28,
28,
26,
27,
27,
27,
27,
27,
26,
26,
27,
27,
25,
26,
26,
27,
26,
26,
27,
26,
27,
26,
25,
26,
26,
28,
27,
27,
26,
26,
26,
28,
28,
28,
28,
27,
29,
29,
30,
30,
30,
30,
32,
33,
33,
34,
34,
34,
34,
34,
33,
32,
33,
32,
33,
33,
31,
31,
31,
30,
31,
30,
28,
29,
28,
29,
28,
28,
27,
28,
27,
27,
27,
27,
27,
26,
28,
27,
27,
26,
26,
26,
28,
26,
26,
26,
26,
26,
27,
28,
27,
27,
28,
29,
27,
27,
31,
29,
28,
31,
30,
29,
30,
31,
31,
30,
35,
31,
33,
31,
33,
34,
35,
32,
31,
31,
31,
30,
31,
30,
30,
30,
28,
27,
29,
30,
27,
29,
30,
23,
29,
26,
28,
26,
25,
24,
26,
26,
26,
26,
25,
25,
27,
27,
27,
27,
27,
26,
29,
27,
27,
28,
30,
29,
27,
28,
28,
28,
28,
29,
29,
29,
29,
30,
30,
30,
29,
32,
31,
33,
32,
32,
29,
33,
31,
30,
29,
29,
29,
26,
26,
30,
28,
25,
27,
27,
22,
28,
25,
28,
26,
24,
24,
23,
24,
23,
28,
23,
24,
25,
22,
24,
24,
25,
24,
21,
25,
25,
25,
24,
24,
23,
26,
23,
21,
29,
24,
28,
19,
30,
24,
34,
25
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
29,
29
],
[
34,
34
],
[
41,
41
],
[
68,
68
],
[
81,
81
],
[
88,
101
],
[
103,
104
],
[
106,
108
],
[
111,
111
],
[
114,
114
],
[
123,
123
],
[
146,
148
],
[
150,
174
],
[
198,
198
],
[
204,
207
],
[
209,
240
],
[
242,
242
],
[
249,
249
],
[
255,
255
],
[
262,
262
],
[
265,
266
],
[
269,
295
],
[
297,
298
],
[
300,
301
],
[
303,
303
],
[
305,
305
],
[
321,
321
],
[
324,
326
],
[
328,
351
],
[
354,
355
],
[
360,
360
],
[
362,
362
],
[
369,
369
],
[
388,
388
],
[
390,
390
],
[
392,
392
],
[
394,
394
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
14,
14,
16,
14,
15,
14,
14,
22,
14,
16,
19,
16,
21,
18,
17,
21,
18,
20,
21,
23,
22,
19,
27,
21,
25,
23,
21,
26,
24,
31,
23,
24,
25,
25,
29,
21,
27,
21,
25,
24,
21,
28,
19,
22,
27,
19,
24,
24,
18,
24,
25,
21,
22,
21,
23,
20,
22,
24,
22,
23,
22,
23,
23,
23,
23,
24,
20,
20,
29,
24,
24,
23,
24,
24,
22,
24,
25,
26,
25,
23,
25,
28,
27,
24,
27,
27,
27,
27,
29,
29,
29,
32,
31,
34,
29,
33,
30,
33,
30,
31,
29,
30,
27,
32,
28,
27,
29,
31,
28,
27,
27,
28,
26,
27,
28,
26,
25,
25,
27,
27,
26,
25,
23,
28,
26,
25,
25,
24,
26,
25,
26,
25,
24,
26,
26,
23,
25,
25,
25,
25,
26,
26,
27,
26,
25,
27,
28,
28,
28,
27,
28,
29,
29,
31,
31,
30,
29,
29,
31,
32,
31,
30,
31,
31,
30,
30,
29,
29,
29,
29,
28,
28,
28,
28,
28,
26,
27,
27,
27,
27,
27,
26,
26,
27,
27,
25,
26,
26,
27,
26,
26,
27,
26,
27,
26,
25,
26,
26,
28,
27,
27,
26,
26,
26,
28,
28,
28,
28,
27,
29,
29,
30,
30,
30,
30,
32,
33,
33,
34,
34,
34,
34,
34,
33,
32,
33,
32,
33,
33,
31,
31,
31,
30,
31,
30,
28,
29,
28,
29,
28,
28,
27,
28,
27,
27,
27,
27,
27,
26,
28,
27,
27,
26,
26,
26,
28,
26,
26,
26,
26,
26,
27,
28,
27,
27,
28,
29,
27,
27,
31,
29,
28,
31,
30,
29,
30,
31,
31,
30,
35,
31,
33,
31,
33,
34,
35,
32,
31,
31,
31,
30,
31,
30,
30,
30,
28,
27,
29,
30,
27,
29,
30,
23,
29,
26,
28,
26,
25,
24,
26,
26,
26,
26,
25,
25,
27,
27,
27,
27,
27,
26,
29,
27,
27,
28,
30,
29,
27,
28,
28,
28,
28,
29,
29,
29,
29,
30,
30,
30,
29,
32,
31,
33,
32,
32,
29,
33,
31,
30,
29,
29,
29,
26,
26,
30,
28,
25,
27,
27,
22,
28,
25,
28,
26,
24,
24,
23,
24,
23,
28,
23,
24,
25,
22,
24,
24,
25,
24,
21,
25,
25,
25,
24,
24,
23,
26,
23,
21,
29,
24,
28,
19,
30,
24,
34,
25
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
6
],
[
8,
9
],
[
11,
11
],
[
13,
14
],
[
16,
16
],
[
48,
48
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
28,
28,
27,
27,
26,
27,
28,
28,
28,
27,
27,
28,
28,
28,
29,
30,
30,
30,
32,
31,
31,
31,
30,
31,
31,
30,
29,
30,
30,
29,
29,
30,
30,
28,
28,
28,
28,
28,
28,
27,
27,
27,
27,
28,
28,
27,
28,
28,
28,
28,
29,
29,
29,
29,
29,
29,
29,
30,
29,
29,
29,
29,
29,
30,
30,
30,
30,
30,
31,
31,
32,
32,
32,
32,
33,
34,
33,
31,
31,
32,
32,
32,
31,
31,
31,
30,
30,
30,
29,
29,
29,
28,
28,
29,
28,
28,
29,
29,
29,
29,
29,
29,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
29,
30,
31,
31,
29,
32,
34,
33,
33,
32,
33,
33,
33,
34,
33,
32,
32,
32,
32,
31,
32,
33,
32,
32,
32,
31,
31,
30,
30,
30,
30,
30,
30,
29,
29,
29,
28,
28,
32,
31,
29,
29,
30,
31,
31,
30,
30,
31,
32,
32,
31,
30,
31,
32,
31,
30,
31,
32,
31,
32,
33,
33,
33,
33,
34,
34,
33,
37,
36,
34,
33,
33,
34,
33,
33,
32,
31,
31,
32,
31,
30,
28,
31,
28,
29,
30,
30,
28,
28,
29,
28,
28,
29,
29,
28,
29,
29,
31,
31,
30,
29,
31,
31,
30,
30,
30,
30,
30,
31,
30,
30,
31,
31,
31,
31,
32,
32,
32,
34,
34,
33,
35,
35,
34,
33,
32,
32,
31,
31,
32,
33,
32,
32,
30,
29,
30,
30,
30,
29,
28,
32,
28,
29,
28,
27,
27,
30,
29,
26,
31,
20,
24,
30,
36,
29,
27,
26,
29,
33,
26,
36,
35,
28,
28,
31,
34,
27,
32,
30,
33,
28,
34,
30,
34,
27,
47,
34,
31,
28,
36,
30
] | {
"1. Frame Length": "The total frame length is: 296.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
28,
28,
27,
27,
26,
27,
28,
28,
28,
27,
27,
28,
28,
28,
29,
30,
30,
30,
32,
31,
31,
31,
30,
31,
31,
30,
29,
30,
30,
29,
29,
30,
30,
28,
28,
28,
28,
28,
28,
27,
27,
27,
27,
28,
28,
27,
28,
28,
28,
28,
29,
29,
29,
29,
29,
29,
29,
30,
29,
29,
29,
29,
29,
30,
30,
30,
30,
30,
31,
31,
32,
32,
32,
32,
33,
34,
33,
31,
31,
32,
32,
32,
31,
31,
31,
30,
30,
30,
29,
29,
29,
28,
28,
29,
28,
28,
29,
29,
29,
29,
29,
29,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
29,
30,
31,
31,
29,
32,
34,
33,
33,
32,
33,
33,
33,
34,
33,
32,
32,
32,
32,
31,
32,
33,
32,
32,
32,
31,
31,
30,
30,
30,
30,
30,
30,
29,
29,
29,
28,
28,
32,
31,
29,
29,
30,
31,
31,
30,
30,
31,
32,
32,
31,
30,
31,
32,
31,
30,
31,
32,
31,
32,
33,
33,
33,
33,
34,
34,
33,
37,
36,
34,
33,
33,
34,
33,
33,
32,
31,
31,
32,
31,
30,
28,
31,
28,
29,
30,
30,
28,
28,
29,
28,
28,
29,
29,
28,
29,
29,
31,
31,
30,
29,
31,
31,
30,
30,
30,
30,
30,
31,
30,
30,
31,
31,
31,
31,
32,
32,
32,
34,
34,
33,
35,
35,
34,
33,
32,
32,
31,
31,
32,
33,
32,
32,
30,
29,
30,
30,
30,
29,
28,
32,
28,
29,
28,
27,
27,
30,
29,
26,
31,
20,
24,
30,
36,
29,
27,
26,
29,
33,
26,
36,
35,
28,
28,
31,
34,
27,
32,
30,
33,
28,
34,
30,
34,
27,
47,
34,
31,
28,
36,
30
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
290,
290
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
28,
28,
27,
27,
26,
27,
28,
28,
28,
27,
27,
28,
28,
28,
29,
30,
30,
30,
32,
31,
31,
31,
30,
31,
31,
30,
29,
30,
30,
29,
29,
30,
30,
28,
28,
28,
28,
28,
28,
27,
27,
27,
27,
28,
28,
27,
28,
28,
28,
28,
29,
29,
29,
29,
29,
29,
29,
30,
29,
29,
29,
29,
29,
30,
30,
30,
30,
30,
31,
31,
32,
32,
32,
32,
33,
34,
33,
31,
31,
32,
32,
32,
31,
31,
31,
30,
30,
30,
29,
29,
29,
28,
28,
29,
28,
28,
29,
29,
29,
29,
29,
29,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
29,
30,
31,
31,
29,
32,
34,
33,
33,
32,
33,
33,
33,
34,
33,
32,
32,
32,
32,
31,
32,
33,
32,
32,
32,
31,
31,
30,
30,
30,
30,
30,
30,
29,
29,
29,
28,
28,
32,
31,
29,
29,
30,
31,
31,
30,
30,
31,
32,
32,
31,
30,
31,
32,
31,
30,
31,
32,
31,
32,
33,
33,
33,
33,
34,
34,
33,
37,
36,
34,
33,
33,
34,
33,
33,
32,
31,
31,
32,
31,
30,
28,
31,
28,
29,
30,
30,
28,
28,
29,
28,
28,
29,
29,
28,
29,
29,
31,
31,
30,
29,
31,
31,
30,
30,
30,
30,
30,
31,
30,
30,
31,
31,
31,
31,
32,
32,
32,
34,
34,
33,
35,
35,
34,
33,
32,
32,
31,
31,
32,
33,
32,
32,
30,
29,
30,
30,
30,
29,
28,
32,
28,
29,
28,
27,
27,
30,
29,
26,
31,
20,
24,
30,
36,
29,
27,
26,
29,
33,
26,
36,
35,
28,
28,
31,
34,
27,
32,
30,
33,
28,
34,
30,
34,
27,
47,
34,
31,
28,
36,
30
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
265,
266
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
0,
0,
1,
0,
0,
0,
1,
1,
0,
1,
1,
1,
0,
0,
1,
1,
1,
1,
1,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
3,
3,
4,
4,
5,
5,
6,
6,
7,
8,
8,
9,
10,
11,
10,
11,
12,
12,
12,
14,
13,
13,
13,
13,
13,
14,
14,
14,
15,
15,
15,
15,
16,
16,
16,
16,
16,
17,
17,
19,
19,
19,
20,
20,
22,
20,
18,
20,
23,
23,
22,
22,
22,
24,
24,
23,
25,
25,
24,
25,
25,
25,
25,
25,
26,
27,
27,
26,
25,
26,
26,
28,
29,
26,
27,
28,
24,
15,
25,
27,
27,
28,
29,
40,
28,
17,
24,
27,
26,
23,
23,
24,
24,
22,
22,
22,
19,
17,
17,
15,
13,
13,
11,
9,
8,
7,
5,
5,
7,
11,
14,
14,
18,
22,
23,
24,
25,
28,
29,
30,
32,
33,
35,
39,
41,
43,
44,
42,
35,
49,
48,
55,
62,
72,
67,
72,
76,
77,
85,
88,
91,
95,
102,
106,
106,
108,
111,
110,
111,
112,
107,
99,
83,
86,
88,
83,
70,
69,
73,
71,
69,
68,
67,
65,
61,
57,
53,
50,
46,
42,
40,
37,
34,
32,
30,
27,
25,
22,
19,
16,
14,
11,
8,
6,
5,
6,
9,
12,
14,
16,
19,
22,
25,
27,
31,
33,
36,
39,
41,
44,
46,
49,
52,
55,
57,
59,
61,
64,
67,
69,
72,
76,
80,
83,
87,
91,
95,
99,
103,
105,
108,
118,
115,
96,
84,
86,
84,
78,
71,
61,
50,
45,
41,
38,
37,
30,
22,
17,
14,
6,
5,
3,
2,
5,
5,
5,
2,
8,
9,
11,
14,
13,
13,
17,
19,
18,
18,
19,
20,
19,
20,
20,
19,
20,
22,
20,
20,
20,
19,
19,
19,
18,
18,
18,
19,
19,
19,
17,
16,
17,
17,
18,
16,
14,
15,
15,
14,
14,
13,
12,
12,
15,
12,
11,
11,
10,
9,
9,
9,
9,
9,
8,
7,
7,
6,
5,
5,
4,
4,
4,
3,
3,
4,
3,
2,
2,
2,
2,
2,
2,
2,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
2,
2,
2,
2,
1,
1,
2,
1,
1,
2,
1,
1,
2
] | {
"1. Frame Length": "The total frame length is: 400.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
0,
0,
1,
0,
0,
0,
1,
1,
0,
1,
1,
1,
0,
0,
1,
1,
1,
1,
1,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
3,
3,
4,
4,
5,
5,
6,
6,
7,
8,
8,
9,
10,
11,
10,
11,
12,
12,
12,
14,
13,
13,
13,
13,
13,
14,
14,
14,
15,
15,
15,
15,
16,
16,
16,
16,
16,
17,
17,
19,
19,
19,
20,
20,
22,
20,
18,
20,
23,
23,
22,
22,
22,
24,
24,
23,
25,
25,
24,
25,
25,
25,
25,
25,
26,
27,
27,
26,
25,
26,
26,
28,
29,
26,
27,
28,
24,
15,
25,
27,
27,
28,
29,
40,
28,
17,
24,
27,
26,
23,
23,
24,
24,
22,
22,
22,
19,
17,
17,
15,
13,
13,
11,
9,
8,
7,
5,
5,
7,
11,
14,
14,
18,
22,
23,
24,
25,
28,
29,
30,
32,
33,
35,
39,
41,
43,
44,
42,
35,
49,
48,
55,
62,
72,
67,
72,
76,
77,
85,
88,
91,
95,
102,
106,
106,
108,
111,
110,
111,
112,
107,
99,
83,
86,
88,
83,
70,
69,
73,
71,
69,
68,
67,
65,
61,
57,
53,
50,
46,
42,
40,
37,
34,
32,
30,
27,
25,
22,
19,
16,
14,
11,
8,
6,
5,
6,
9,
12,
14,
16,
19,
22,
25,
27,
31,
33,
36,
39,
41,
44,
46,
49,
52,
55,
57,
59,
61,
64,
67,
69,
72,
76,
80,
83,
87,
91,
95,
99,
103,
105,
108,
118,
115,
96,
84,
86,
84,
78,
71,
61,
50,
45,
41,
38,
37,
30,
22,
17,
14,
6,
5,
3,
2,
5,
5,
5,
2,
8,
9,
11,
14,
13,
13,
17,
19,
18,
18,
19,
20,
19,
20,
20,
19,
20,
22,
20,
20,
20,
19,
19,
19,
18,
18,
18,
19,
19,
19,
17,
16,
17,
17,
18,
16,
14,
15,
15,
14,
14,
13,
12,
12,
15,
12,
11,
11,
10,
9,
9,
9,
9,
9,
8,
7,
7,
6,
5,
5,
4,
4,
4,
3,
3,
4,
3,
2,
2,
2,
2,
2,
2,
2,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
2,
2,
2,
2,
1,
1,
2,
1,
1,
2,
1,
1,
2
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
175,
185
],
[
250,
257
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
0,
0,
1,
0,
0,
0,
1,
1,
0,
1,
1,
1,
0,
0,
1,
1,
1,
1,
1,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
3,
3,
4,
4,
5,
5,
6,
6,
7,
8,
8,
9,
10,
11,
10,
11,
12,
12,
12,
14,
13,
13,
13,
13,
13,
14,
14,
14,
15,
15,
15,
15,
16,
16,
16,
16,
16,
17,
17,
19,
19,
19,
20,
20,
22,
20,
18,
20,
23,
23,
22,
22,
22,
24,
24,
23,
25,
25,
24,
25,
25,
25,
25,
25,
26,
27,
27,
26,
25,
26,
26,
28,
29,
26,
27,
28,
24,
15,
25,
27,
27,
28,
29,
40,
28,
17,
24,
27,
26,
23,
23,
24,
24,
22,
22,
22,
19,
17,
17,
15,
13,
13,
11,
9,
8,
7,
5,
5,
7,
11,
14,
14,
18,
22,
23,
24,
25,
28,
29,
30,
32,
33,
35,
39,
41,
43,
44,
42,
35,
49,
48,
55,
62,
72,
67,
72,
76,
77,
85,
88,
91,
95,
102,
106,
106,
108,
111,
110,
111,
112,
107,
99,
83,
86,
88,
83,
70,
69,
73,
71,
69,
68,
67,
65,
61,
57,
53,
50,
46,
42,
40,
37,
34,
32,
30,
27,
25,
22,
19,
16,
14,
11,
8,
6,
5,
6,
9,
12,
14,
16,
19,
22,
25,
27,
31,
33,
36,
39,
41,
44,
46,
49,
52,
55,
57,
59,
61,
64,
67,
69,
72,
76,
80,
83,
87,
91,
95,
99,
103,
105,
108,
118,
115,
96,
84,
86,
84,
78,
71,
61,
50,
45,
41,
38,
37,
30,
22,
17,
14,
6,
5,
3,
2,
5,
5,
5,
2,
8,
9,
11,
14,
13,
13,
17,
19,
18,
18,
19,
20,
19,
20,
20,
19,
20,
22,
20,
20,
20,
19,
19,
19,
18,
18,
18,
19,
19,
19,
17,
16,
17,
17,
18,
16,
14,
15,
15,
14,
14,
13,
12,
12,
15,
12,
11,
11,
10,
9,
9,
9,
9,
9,
8,
7,
7,
6,
5,
5,
4,
4,
4,
3,
3,
4,
3,
2,
2,
2,
2,
2,
2,
2,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
2,
2,
2,
2,
1,
1,
2,
1,
1,
2,
1,
1,
2
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
86
],
[
89,
89
],
[
111,
111
],
[
119,
119
],
[
123,
124
],
[
127,
148
],
[
211,
225
],
[
270,
399
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
1,
1,
3,
2,
1,
1,
1,
2,
2,
0,
2,
1,
3,
2,
1,
1,
1,
1,
2,
3,
1,
1,
2,
1,
0,
2,
2,
0,
1,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
0,
0,
1,
1,
1,
0,
1,
0,
0,
1,
1,
0,
0,
0,
0,
1,
1,
0,
0,
0,
1,
1,
0,
1,
0,
0,
1,
1,
0,
0,
0,
0,
0,
1,
2,
1,
1,
1,
1,
1,
4,
3,
0,
0,
0,
0,
0,
0,
0,
1,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
0,
0,
0,
1,
1,
0,
0,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
0,
0,
0,
1,
1,
1,
1,
1,
1,
0,
0,
0,
1,
1,
1,
1,
0,
0,
0,
1,
1,
1,
0,
0,
1,
1,
1,
0,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
0,
0,
0,
1,
0,
0,
0,
0,
1,
1,
0,
0,
0,
0,
1,
0,
0,
1,
1,
0,
1,
0,
0,
0,
0,
0,
0,
1,
1,
0,
0,
0,
0,
1,
1,
1,
1,
1,
0,
1,
1,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
1,
1,
0,
1,
1,
0,
0,
0,
1,
0,
0,
0,
0,
0,
1,
0,
0,
1,
1,
1,
0,
0,
0,
0,
1,
1,
1,
1,
1,
0,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
2,
1,
1,
1,
1,
2,
2,
1,
1,
2,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
0,
0,
1,
1,
0,
0,
1,
1,
1,
1,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
0,
0,
1,
1,
1,
1,
2,
2,
2,
2,
1,
1,
1,
2,
2,
2,
2,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
0,
1,
2,
2,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
1,
0,
0,
1,
2,
1,
1,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1
] | {
"1. Frame Length": "The total frame length is: 513.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
1,
1,
3,
2,
1,
1,
1,
2,
2,
0,
2,
1,
3,
2,
1,
1,
1,
1,
2,
3,
1,
1,
2,
1,
0,
2,
2,
0,
1,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
0,
0,
1,
1,
1,
0,
1,
0,
0,
1,
1,
0,
0,
0,
0,
1,
1,
0,
0,
0,
1,
1,
0,
1,
0,
0,
1,
1,
0,
0,
0,
0,
0,
1,
2,
1,
1,
1,
1,
1,
4,
3,
0,
0,
0,
0,
0,
0,
0,
1,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
0,
0,
0,
1,
1,
0,
0,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
0,
0,
0,
1,
1,
1,
1,
1,
1,
0,
0,
0,
1,
1,
1,
1,
0,
0,
0,
1,
1,
1,
0,
0,
1,
1,
1,
0,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
0,
0,
0,
1,
0,
0,
0,
0,
1,
1,
0,
0,
0,
0,
1,
0,
0,
1,
1,
0,
1,
0,
0,
0,
0,
0,
0,
1,
1,
0,
0,
0,
0,
1,
1,
1,
1,
1,
0,
1,
1,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
1,
1,
0,
1,
1,
0,
0,
0,
1,
0,
0,
0,
0,
0,
1,
0,
0,
1,
1,
1,
0,
0,
0,
0,
1,
1,
1,
1,
1,
0,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
2,
1,
1,
1,
1,
2,
2,
1,
1,
2,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
0,
0,
1,
1,
0,
0,
1,
1,
1,
1,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
0,
0,
1,
1,
1,
1,
2,
2,
2,
2,
1,
1,
1,
2,
2,
2,
2,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
0,
1,
2,
2,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
1,
0,
0,
1,
2,
1,
1,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
99,
99
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
1,
1,
3,
2,
1,
1,
1,
2,
2,
0,
2,
1,
3,
2,
1,
1,
1,
1,
2,
3,
1,
1,
2,
1,
0,
2,
2,
0,
1,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
0,
0,
1,
1,
1,
0,
1,
0,
0,
1,
1,
0,
0,
0,
0,
1,
1,
0,
0,
0,
1,
1,
0,
1,
0,
0,
1,
1,
0,
0,
0,
0,
0,
1,
2,
1,
1,
1,
1,
1,
4,
3,
0,
0,
0,
0,
0,
0,
0,
1,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
0,
0,
0,
1,
1,
0,
0,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
0,
0,
0,
1,
1,
1,
1,
1,
1,
0,
0,
0,
1,
1,
1,
1,
0,
0,
0,
1,
1,
1,
0,
0,
1,
1,
1,
0,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
0,
0,
0,
1,
0,
0,
0,
0,
1,
1,
0,
0,
0,
0,
1,
0,
0,
1,
1,
0,
1,
0,
0,
0,
0,
0,
0,
1,
1,
0,
0,
0,
0,
1,
1,
1,
1,
1,
0,
1,
1,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
1,
1,
0,
1,
1,
0,
0,
0,
1,
0,
0,
0,
0,
0,
1,
0,
0,
1,
1,
1,
0,
0,
0,
0,
1,
1,
1,
1,
1,
0,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
2,
1,
1,
1,
1,
2,
2,
1,
1,
2,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
0,
0,
1,
1,
0,
0,
1,
1,
1,
1,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
0,
0,
1,
1,
1,
1,
2,
2,
2,
2,
1,
1,
1,
2,
2,
2,
2,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
0,
1,
2,
2,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
1,
0,
0,
1,
2,
1,
1,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
9,
9
],
[
24,
24
],
[
27,
27
],
[
29,
35
],
[
37,
40
],
[
42,
42
],
[
54,
54
],
[
59,
60
],
[
64,
64
],
[
66,
67
],
[
70,
73
],
[
76,
78
],
[
81,
81
],
[
83,
84
],
[
87,
91
],
[
101,
107
],
[
109,
109
],
[
111,
118
],
[
121,
123
],
[
126,
127
],
[
135,
136
],
[
139,
139
],
[
156,
157
],
[
167,
167
],
[
171,
173
],
[
180,
182
],
[
187,
189
],
[
193,
194
],
[
198,
200
],
[
203,
208
],
[
211,
225
],
[
228,
230
],
[
232,
235
],
[
238,
241
],
[
243,
244
],
[
247,
247
],
[
249,
254
],
[
257,
260
],
[
266,
266
],
[
269,
272
],
[
274,
279
],
[
282,
282
],
[
285,
287
],
[
289,
293
],
[
295,
296
],
[
300,
303
],
[
309,
309
],
[
312,
312
],
[
328,
328
],
[
362,
362
],
[
366,
367
],
[
370,
371
],
[
376,
377
],
[
387,
387
],
[
398,
399
],
[
438,
438
],
[
458,
459
],
[
463,
464
],
[
469,
472
],
[
479,
485
],
[
487,
493
],
[
495,
497
],
[
503,
503
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
26,
26,
28,
30,
29,
27,
26,
26,
28,
28,
27,
28,
29,
28,
27,
26,
27,
29,
29,
28,
28,
28,
28,
29,
30,
29,
28,
28,
30,
30,
29,
30,
30,
31,
32,
32,
33,
33,
33,
33,
32,
32,
33,
32,
31,
31,
32,
31,
30,
30,
30,
30,
29,
27,
27,
27,
27,
27,
27,
26,
26,
27,
27,
26,
26,
26,
26,
25,
26,
25,
25,
26,
26,
25,
26,
27,
27,
26,
26,
27,
28,
26,
26,
26,
28,
28,
27,
28,
28,
29,
28,
28,
29,
29,
29,
29,
29,
29,
29,
29,
29,
30,
32,
32,
32,
33,
33,
33,
34,
33,
32,
32,
32,
32,
32,
32,
31,
30,
30,
29,
29,
29,
29,
29,
28,
26,
28,
27,
26,
27,
27,
28,
28,
26,
26,
27,
27,
27,
28,
27,
27,
28,
28,
27,
28,
29,
28,
28,
29,
29,
29,
29,
29,
30,
30,
29,
30,
30,
30,
29,
30,
31,
31,
31,
32,
32,
32,
34,
35,
34,
34,
34,
34,
33,
34,
32,
32,
33,
32,
33,
32,
32,
31,
30,
28,
30,
29,
28,
28,
29,
29,
28,
28,
28,
27,
26,
27,
27,
27,
27,
28,
28,
27,
27,
26,
27,
28,
28,
28,
28,
27,
27,
29,
29,
28,
28,
28,
29,
29,
30,
31,
30,
30,
30,
30,
31,
31,
31,
30,
31,
31,
32,
32,
33,
34,
36,
36,
35,
34,
34,
34,
33,
33,
33,
32,
32,
31,
30,
31,
31,
31,
30,
28,
29,
29,
29,
28,
28,
27,
28,
28,
27,
27,
28,
28,
28,
27,
27,
28,
28,
28,
29,
29,
28,
28,
29,
29,
28,
29,
30,
29,
28,
28,
30,
31,
29,
29,
30,
28,
29,
30,
31,
30,
31,
32,
33,
32,
34,
34,
34,
34,
35,
36,
35,
33,
33,
34,
34,
33,
33,
33,
32,
33,
33,
31,
30,
31,
30,
30,
29,
27,
29,
30,
29,
28,
26,
27,
28,
28,
29,
27,
27,
27,
27,
27,
28,
29,
29,
28,
26,
27,
29
] | {
"1. Frame Length": "The total frame length is: 342.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
26,
26,
28,
30,
29,
27,
26,
26,
28,
28,
27,
28,
29,
28,
27,
26,
27,
29,
29,
28,
28,
28,
28,
29,
30,
29,
28,
28,
30,
30,
29,
30,
30,
31,
32,
32,
33,
33,
33,
33,
32,
32,
33,
32,
31,
31,
32,
31,
30,
30,
30,
30,
29,
27,
27,
27,
27,
27,
27,
26,
26,
27,
27,
26,
26,
26,
26,
25,
26,
25,
25,
26,
26,
25,
26,
27,
27,
26,
26,
27,
28,
26,
26,
26,
28,
28,
27,
28,
28,
29,
28,
28,
29,
29,
29,
29,
29,
29,
29,
29,
29,
30,
32,
32,
32,
33,
33,
33,
34,
33,
32,
32,
32,
32,
32,
32,
31,
30,
30,
29,
29,
29,
29,
29,
28,
26,
28,
27,
26,
27,
27,
28,
28,
26,
26,
27,
27,
27,
28,
27,
27,
28,
28,
27,
28,
29,
28,
28,
29,
29,
29,
29,
29,
30,
30,
29,
30,
30,
30,
29,
30,
31,
31,
31,
32,
32,
32,
34,
35,
34,
34,
34,
34,
33,
34,
32,
32,
33,
32,
33,
32,
32,
31,
30,
28,
30,
29,
28,
28,
29,
29,
28,
28,
28,
27,
26,
27,
27,
27,
27,
28,
28,
27,
27,
26,
27,
28,
28,
28,
28,
27,
27,
29,
29,
28,
28,
28,
29,
29,
30,
31,
30,
30,
30,
30,
31,
31,
31,
30,
31,
31,
32,
32,
33,
34,
36,
36,
35,
34,
34,
34,
33,
33,
33,
32,
32,
31,
30,
31,
31,
31,
30,
28,
29,
29,
29,
28,
28,
27,
28,
28,
27,
27,
28,
28,
28,
27,
27,
28,
28,
28,
29,
29,
28,
28,
29,
29,
28,
29,
30,
29,
28,
28,
30,
31,
29,
29,
30,
28,
29,
30,
31,
30,
31,
32,
33,
32,
34,
34,
34,
34,
35,
36,
35,
33,
33,
34,
34,
33,
33,
33,
32,
33,
33,
31,
30,
31,
30,
30,
29,
27,
29,
30,
29,
28,
26,
27,
28,
28,
29,
27,
27,
27,
27,
27,
28,
29,
29,
28,
26,
27,
29
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
3,
4
],
[
12,
12
],
[
17,
18
],
[
23,
25
],
[
28,
52
],
[
89,
89
],
[
92,
123
],
[
145,
145
],
[
148,
183
],
[
185,
186
],
[
189,
190
],
[
212,
213
],
[
217,
251
],
[
253,
255
],
[
271,
272
],
[
275,
276
],
[
278,
280
],
[
283,
287
],
[
289,
319
],
[
321,
323
],
[
329,
329
],
[
336,
337
],
[
341,
341
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
26,
26,
28,
30,
29,
27,
26,
26,
28,
28,
27,
28,
29,
28,
27,
26,
27,
29,
29,
28,
28,
28,
28,
29,
30,
29,
28,
28,
30,
30,
29,
30,
30,
31,
32,
32,
33,
33,
33,
33,
32,
32,
33,
32,
31,
31,
32,
31,
30,
30,
30,
30,
29,
27,
27,
27,
27,
27,
27,
26,
26,
27,
27,
26,
26,
26,
26,
25,
26,
25,
25,
26,
26,
25,
26,
27,
27,
26,
26,
27,
28,
26,
26,
26,
28,
28,
27,
28,
28,
29,
28,
28,
29,
29,
29,
29,
29,
29,
29,
29,
29,
30,
32,
32,
32,
33,
33,
33,
34,
33,
32,
32,
32,
32,
32,
32,
31,
30,
30,
29,
29,
29,
29,
29,
28,
26,
28,
27,
26,
27,
27,
28,
28,
26,
26,
27,
27,
27,
28,
27,
27,
28,
28,
27,
28,
29,
28,
28,
29,
29,
29,
29,
29,
30,
30,
29,
30,
30,
30,
29,
30,
31,
31,
31,
32,
32,
32,
34,
35,
34,
34,
34,
34,
33,
34,
32,
32,
33,
32,
33,
32,
32,
31,
30,
28,
30,
29,
28,
28,
29,
29,
28,
28,
28,
27,
26,
27,
27,
27,
27,
28,
28,
27,
27,
26,
27,
28,
28,
28,
28,
27,
27,
29,
29,
28,
28,
28,
29,
29,
30,
31,
30,
30,
30,
30,
31,
31,
31,
30,
31,
31,
32,
32,
33,
34,
36,
36,
35,
34,
34,
34,
33,
33,
33,
32,
32,
31,
30,
31,
31,
31,
30,
28,
29,
29,
29,
28,
28,
27,
28,
28,
27,
27,
28,
28,
28,
27,
27,
28,
28,
28,
29,
29,
28,
28,
29,
29,
28,
29,
30,
29,
28,
28,
30,
31,
29,
29,
30,
28,
29,
30,
31,
30,
31,
32,
33,
32,
34,
34,
34,
34,
35,
36,
35,
33,
33,
34,
34,
33,
33,
33,
32,
33,
33,
31,
30,
31,
30,
30,
29,
27,
29,
30,
29,
28,
26,
27,
28,
28,
29,
27,
27,
27,
27,
27,
28,
29,
29,
28,
26,
27,
29
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
1
],
[
5,
7
],
[
10,
10
],
[
14,
16
],
[
53,
79
],
[
81,
83
],
[
86,
86
],
[
125,
125
],
[
127,
130
],
[
133,
137
],
[
139,
140
],
[
143,
143
],
[
194,
199
],
[
202,
205
],
[
210,
211
],
[
258,
258
],
[
261,
262
],
[
266,
267
],
[
320,
320
],
[
325,
326
],
[
330,
334
],
[
339,
340
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
63,
63,
53,
66,
57,
56,
53,
49,
66,
57,
57,
57,
58,
59,
60,
60,
59,
60,
61,
62,
62,
62,
65,
65,
63,
62,
62,
57,
71,
61,
61,
62,
62,
61,
60,
60,
62,
61,
61,
61,
62,
62,
61,
61,
60,
59,
58,
55,
56,
55,
52,
53,
54,
53,
55,
53,
54,
55,
58,
60,
60,
64,
60,
62,
67,
61,
61,
66,
71,
69,
65,
65,
65,
64,
63,
62,
61,
61,
62,
61,
59,
58,
60,
61,
62,
63,
62,
59,
61,
61,
66,
60,
59,
56,
54,
52,
56,
49,
60,
58,
56,
55,
56,
55,
60,
58,
57,
58,
62,
61,
62,
60,
61,
61,
61,
63,
62,
57,
55,
61,
62,
64,
49,
58,
62,
57,
59,
59,
59,
59,
58,
58,
57,
59,
58,
57,
55,
55,
55,
55,
53,
51,
53,
54,
53,
54,
54,
56,
53,
59,
60,
61,
61,
62,
62,
56,
66,
65,
63,
63,
58,
67,
63,
62,
60,
61,
60,
59
] | {
"1. Frame Length": "The total frame length is: 168.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
63,
63,
53,
66,
57,
56,
53,
49,
66,
57,
57,
57,
58,
59,
60,
60,
59,
60,
61,
62,
62,
62,
65,
65,
63,
62,
62,
57,
71,
61,
61,
62,
62,
61,
60,
60,
62,
61,
61,
61,
62,
62,
61,
61,
60,
59,
58,
55,
56,
55,
52,
53,
54,
53,
55,
53,
54,
55,
58,
60,
60,
64,
60,
62,
67,
61,
61,
66,
71,
69,
65,
65,
65,
64,
63,
62,
61,
61,
62,
61,
59,
58,
60,
61,
62,
63,
62,
59,
61,
61,
66,
60,
59,
56,
54,
52,
56,
49,
60,
58,
56,
55,
56,
55,
60,
58,
57,
58,
62,
61,
62,
60,
61,
61,
61,
63,
62,
57,
55,
61,
62,
64,
49,
58,
62,
57,
59,
59,
59,
59,
58,
58,
57,
59,
58,
57,
55,
55,
55,
55,
53,
51,
53,
54,
53,
54,
54,
56,
53,
59,
60,
61,
61,
62,
62,
56,
66,
65,
63,
63,
58,
67,
63,
62,
60,
61,
60,
59
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
0,
1
],
[
3,
4
],
[
8,
46
],
[
58,
92
],
[
98,
99
],
[
104,
117
],
[
119,
121
],
[
123,
135
],
[
149,
154
],
[
156,
167
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
63,
63,
53,
66,
57,
56,
53,
49,
66,
57,
57,
57,
58,
59,
60,
60,
59,
60,
61,
62,
62,
62,
65,
65,
63,
62,
62,
57,
71,
61,
61,
62,
62,
61,
60,
60,
62,
61,
61,
61,
62,
62,
61,
61,
60,
59,
58,
55,
56,
55,
52,
53,
54,
53,
55,
53,
54,
55,
58,
60,
60,
64,
60,
62,
67,
61,
61,
66,
71,
69,
65,
65,
65,
64,
63,
62,
61,
61,
62,
61,
59,
58,
60,
61,
62,
63,
62,
59,
61,
61,
66,
60,
59,
56,
54,
52,
56,
49,
60,
58,
56,
55,
56,
55,
60,
58,
57,
58,
62,
61,
62,
60,
61,
61,
61,
63,
62,
57,
55,
61,
62,
64,
49,
58,
62,
57,
59,
59,
59,
59,
58,
58,
57,
59,
58,
57,
55,
55,
55,
55,
53,
51,
53,
54,
53,
54,
54,
56,
53,
59,
60,
61,
61,
62,
62,
56,
66,
65,
63,
63,
58,
67,
63,
62,
60,
61,
60,
59
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
2,
2
],
[
6,
7
],
[
50,
51
],
[
53,
53
],
[
55,
55
],
[
95,
95
],
[
97,
97
],
[
122,
122
],
[
140,
142
],
[
144,
144
],
[
148,
148
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
7,
7,
6,
4,
3,
4,
6,
7,
7,
9,
12,
15,
17,
18,
20,
20,
23,
26,
29,
31,
31,
33,
35,
36,
39,
43,
46,
49,
48,
45,
42,
41,
42,
40,
36,
34,
29,
24,
22,
18,
13,
6,
6,
2,
2,
5,
5,
13,
17,
21,
26,
31,
33,
35,
38,
41,
43,
45,
47,
48,
47,
44,
43,
42,
39,
35,
30,
27,
24,
24,
23,
21,
18,
16,
15,
12,
9,
7,
7,
3,
1,
0,
3,
6,
7,
7,
10,
13,
15,
14,
17,
23,
25,
24,
26,
29,
32,
34,
37,
38,
36,
38,
40,
40,
38,
37,
35,
31,
27,
24,
20,
16,
13,
8,
2,
3,
7,
11,
16,
20,
24,
28,
30,
34,
38,
39,
41,
43,
43,
41,
38,
36,
31,
27,
26,
26,
24,
23,
22,
20,
17,
14,
11,
11,
9,
6,
3,
3,
2,
4,
6,
6,
7,
10,
11,
11,
16,
19,
20,
22,
24,
25,
28,
30,
32,
34,
36,
40,
41,
42,
43,
41,
40,
40,
35,
30,
26,
23,
20,
15,
11,
7,
8,
15,
18,
21,
24,
29,
32,
35,
38,
42,
44,
45,
43,
41,
42,
38,
32,
30,
29,
27,
25,
23,
22,
21,
17,
15,
16,
14,
11,
8,
8,
10,
9,
10,
10,
12,
13,
16,
19,
20,
20,
22,
25,
25,
27,
30,
32,
35,
36,
37,
36,
39,
38,
36,
36,
33,
27,
23,
18,
14,
8,
6,
8,
12,
16,
20,
25,
29,
33,
37,
40,
42,
44,
45,
45,
42,
40,
37,
31,
28,
30,
28,
25,
22,
21,
21,
19,
15,
14,
13,
10,
8,
7,
6,
6,
6,
6,
8,
8,
10,
13,
15,
15,
17,
19,
21,
24,
25,
26,
29,
33,
34,
33,
35,
40,
42,
44,
46,
49,
48,
46,
43,
41,
41,
38,
34,
30,
25,
18,
15,
13,
8,
1,
7,
13,
15,
21,
26,
30,
34,
39,
43,
45,
46,
47,
49,
49,
46,
42,
39,
35,
31,
30,
30,
28,
27,
24,
21,
20,
20,
17,
12,
12,
11,
7,
5,
3,
4,
3,
2,
7,
9,
8,
9,
13,
15,
15,
18,
19,
19,
22,
25,
28,
29,
30,
36,
38,
38,
39,
28,
29,
29,
30,
29,
25,
23,
17,
11,
9,
9,
6,
0,
3,
4,
7,
8,
10,
11,
12,
10,
9,
11,
12,
12,
10,
12,
13,
10,
8,
5,
9,
6,
4,
2,
3,
3,
2,
3,
3,
3,
4,
3,
3,
2,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
4
] | {
"1. Frame Length": "The total frame length is: 432.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
7,
7,
6,
4,
3,
4,
6,
7,
7,
9,
12,
15,
17,
18,
20,
20,
23,
26,
29,
31,
31,
33,
35,
36,
39,
43,
46,
49,
48,
45,
42,
41,
42,
40,
36,
34,
29,
24,
22,
18,
13,
6,
6,
2,
2,
5,
5,
13,
17,
21,
26,
31,
33,
35,
38,
41,
43,
45,
47,
48,
47,
44,
43,
42,
39,
35,
30,
27,
24,
24,
23,
21,
18,
16,
15,
12,
9,
7,
7,
3,
1,
0,
3,
6,
7,
7,
10,
13,
15,
14,
17,
23,
25,
24,
26,
29,
32,
34,
37,
38,
36,
38,
40,
40,
38,
37,
35,
31,
27,
24,
20,
16,
13,
8,
2,
3,
7,
11,
16,
20,
24,
28,
30,
34,
38,
39,
41,
43,
43,
41,
38,
36,
31,
27,
26,
26,
24,
23,
22,
20,
17,
14,
11,
11,
9,
6,
3,
3,
2,
4,
6,
6,
7,
10,
11,
11,
16,
19,
20,
22,
24,
25,
28,
30,
32,
34,
36,
40,
41,
42,
43,
41,
40,
40,
35,
30,
26,
23,
20,
15,
11,
7,
8,
15,
18,
21,
24,
29,
32,
35,
38,
42,
44,
45,
43,
41,
42,
38,
32,
30,
29,
27,
25,
23,
22,
21,
17,
15,
16,
14,
11,
8,
8,
10,
9,
10,
10,
12,
13,
16,
19,
20,
20,
22,
25,
25,
27,
30,
32,
35,
36,
37,
36,
39,
38,
36,
36,
33,
27,
23,
18,
14,
8,
6,
8,
12,
16,
20,
25,
29,
33,
37,
40,
42,
44,
45,
45,
42,
40,
37,
31,
28,
30,
28,
25,
22,
21,
21,
19,
15,
14,
13,
10,
8,
7,
6,
6,
6,
6,
8,
8,
10,
13,
15,
15,
17,
19,
21,
24,
25,
26,
29,
33,
34,
33,
35,
40,
42,
44,
46,
49,
48,
46,
43,
41,
41,
38,
34,
30,
25,
18,
15,
13,
8,
1,
7,
13,
15,
21,
26,
30,
34,
39,
43,
45,
46,
47,
49,
49,
46,
42,
39,
35,
31,
30,
30,
28,
27,
24,
21,
20,
20,
17,
12,
12,
11,
7,
5,
3,
4,
3,
2,
7,
9,
8,
9,
13,
15,
15,
18,
19,
19,
22,
25,
28,
29,
30,
36,
38,
38,
39,
28,
29,
29,
30,
29,
25,
23,
17,
11,
9,
9,
6,
0,
3,
4,
7,
8,
10,
11,
12,
10,
9,
11,
12,
12,
10,
12,
13,
10,
8,
5,
9,
6,
4,
2,
3,
3,
2,
3,
3,
3,
4,
3,
3,
2,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
4
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
25,
33
],
[
55,
63
],
[
102,
103
],
[
126,
129
],
[
167,
173
],
[
191,
196
],
[
252,
258
],
[
296,
305
],
[
323,
330
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
7,
7,
6,
4,
3,
4,
6,
7,
7,
9,
12,
15,
17,
18,
20,
20,
23,
26,
29,
31,
31,
33,
35,
36,
39,
43,
46,
49,
48,
45,
42,
41,
42,
40,
36,
34,
29,
24,
22,
18,
13,
6,
6,
2,
2,
5,
5,
13,
17,
21,
26,
31,
33,
35,
38,
41,
43,
45,
47,
48,
47,
44,
43,
42,
39,
35,
30,
27,
24,
24,
23,
21,
18,
16,
15,
12,
9,
7,
7,
3,
1,
0,
3,
6,
7,
7,
10,
13,
15,
14,
17,
23,
25,
24,
26,
29,
32,
34,
37,
38,
36,
38,
40,
40,
38,
37,
35,
31,
27,
24,
20,
16,
13,
8,
2,
3,
7,
11,
16,
20,
24,
28,
30,
34,
38,
39,
41,
43,
43,
41,
38,
36,
31,
27,
26,
26,
24,
23,
22,
20,
17,
14,
11,
11,
9,
6,
3,
3,
2,
4,
6,
6,
7,
10,
11,
11,
16,
19,
20,
22,
24,
25,
28,
30,
32,
34,
36,
40,
41,
42,
43,
41,
40,
40,
35,
30,
26,
23,
20,
15,
11,
7,
8,
15,
18,
21,
24,
29,
32,
35,
38,
42,
44,
45,
43,
41,
42,
38,
32,
30,
29,
27,
25,
23,
22,
21,
17,
15,
16,
14,
11,
8,
8,
10,
9,
10,
10,
12,
13,
16,
19,
20,
20,
22,
25,
25,
27,
30,
32,
35,
36,
37,
36,
39,
38,
36,
36,
33,
27,
23,
18,
14,
8,
6,
8,
12,
16,
20,
25,
29,
33,
37,
40,
42,
44,
45,
45,
42,
40,
37,
31,
28,
30,
28,
25,
22,
21,
21,
19,
15,
14,
13,
10,
8,
7,
6,
6,
6,
6,
8,
8,
10,
13,
15,
15,
17,
19,
21,
24,
25,
26,
29,
33,
34,
33,
35,
40,
42,
44,
46,
49,
48,
46,
43,
41,
41,
38,
34,
30,
25,
18,
15,
13,
8,
1,
7,
13,
15,
21,
26,
30,
34,
39,
43,
45,
46,
47,
49,
49,
46,
42,
39,
35,
31,
30,
30,
28,
27,
24,
21,
20,
20,
17,
12,
12,
11,
7,
5,
3,
4,
3,
2,
7,
9,
8,
9,
13,
15,
15,
18,
19,
19,
22,
25,
28,
29,
30,
36,
38,
38,
39,
28,
29,
29,
30,
29,
25,
23,
17,
11,
9,
9,
6,
0,
3,
4,
7,
8,
10,
11,
12,
10,
9,
11,
12,
12,
10,
12,
13,
10,
8,
5,
9,
6,
4,
2,
3,
3,
2,
3,
3,
3,
4,
3,
3,
2,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
4
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
9
],
[
41,
46
],
[
76,
85
],
[
113,
116
],
[
144,
152
],
[
181,
182
],
[
211,
212
],
[
214,
214
],
[
242,
244
],
[
273,
280
],
[
313,
315
],
[
346,
355
],
[
380,
387
],
[
392,
392
],
[
400,
431
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
9,
9,
8,
9,
9,
9,
9,
10,
10,
10,
10,
10,
11,
11,
11,
11,
11,
11,
12,
12,
12,
12,
13,
13,
13,
13,
13,
14,
14,
14,
14,
15,
15,
15,
15,
15,
15,
15,
16,
16,
16,
16,
17,
16,
16,
16,
17,
17,
17,
17,
17,
17,
16,
16,
17,
17,
16,
17,
17,
16,
16,
16,
16,
16,
16,
16,
15,
15,
15,
15,
15,
15,
15,
14,
13,
14,
14,
13,
13,
13,
13,
13,
13,
13,
12,
12,
13,
12,
12,
13,
12,
12,
12,
12,
12,
12,
12,
12,
12,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
11,
11,
11,
11,
11,
12,
12,
12,
13,
12,
12,
13,
15,
14,
13,
13,
15,
15,
14,
14,
14,
14,
16,
16,
16,
16,
16,
16,
16,
16,
17,
17,
17,
17,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
17,
17,
17,
17,
17,
17,
16,
16,
15,
15,
15,
15,
15,
15,
14,
14,
14,
14,
13,
13,
13,
13,
13,
13,
12,
11,
12,
12,
13,
15,
12,
10,
13,
13,
11,
11,
11,
11,
10,
11,
11,
11,
10,
10,
10,
11,
11,
11,
10,
11,
11,
10,
10,
11,
11,
11,
10,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
12,
12,
12,
12,
12,
12,
12,
12,
13,
13,
13,
13,
13,
13,
13,
14,
14,
14,
14,
14,
14,
15,
15,
16,
16,
16,
16,
16,
17,
17,
17,
18,
18,
18,
18,
18,
19,
19,
19,
19,
18,
18,
18,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
18,
17,
18,
19,
18,
18,
17,
18,
17,
17,
16,
16,
17,
17,
16,
16,
15,
15,
15,
15,
15,
15,
15,
15,
14,
14,
14,
14,
14,
14,
14,
13,
13,
13,
13,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
11,
11,
12,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
10,
10,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
11,
10,
10,
11,
11,
10,
11,
11,
11,
11,
11,
11,
12,
12,
12,
12,
12,
12,
12,
12,
12,
13,
15,
14,
14,
14,
14,
14,
15,
15,
15,
15,
15,
15,
15,
15,
15,
15,
15,
16,
16,
16,
16,
15,
16,
16,
15,
15,
15,
15,
15,
15,
14,
14,
15,
14,
14,
14,
13,
13,
12,
12,
12,
11,
11,
12,
11,
10,
11,
11,
10,
10,
10,
10,
9,
9,
9,
9,
8,
8,
9,
8,
8,
8,
8,
9,
8,
7,
7,
7,
7,
6,
6,
7,
7,
7,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
6,
6,
5,
6,
6,
5,
6,
6,
5,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
6,
7,
8,
7,
7,
7,
7,
7,
8,
8,
8,
9,
8,
7,
7,
8,
8,
8,
8,
8,
8,
8,
9,
8,
8,
9,
9,
8,
8,
9,
9,
9,
10,
8,
9,
9,
9,
9,
9,
9,
9,
9,
8,
7,
8,
9,
9,
8,
8,
8,
9,
8,
7,
7,
8,
7,
7,
7,
7,
6,
5,
6,
7,
6,
5,
6,
5,
5,
4,
4,
4,
5,
4,
4,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
1,
2,
3,
2,
3,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
4,
3,
3,
3,
3,
4,
4,
4,
5,
6,
6,
5,
5,
5,
5,
6,
5,
6,
6,
7,
8,
7,
7,
8,
8,
9,
10,
10,
9,
10,
10,
11,
11,
11,
12,
12,
12,
12,
13,
13,
14,
14,
15,
15,
15,
16,
17,
17,
17,
17,
17,
18,
18,
18,
18,
19,
19,
19,
19,
19,
19,
20,
20,
20,
20,
19,
19,
19,
19,
19,
18,
18,
18,
17,
17,
17,
17,
17,
17,
16,
15,
15,
16,
15,
14,
14,
14,
14,
14,
14,
13,
13,
13,
13,
13,
13,
13,
13,
12,
11,
12,
12,
12,
14,
13,
12,
12,
12,
12,
12,
13,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
13,
13,
12,
12,
13,
13,
13,
13,
13,
13,
14,
13,
13,
14,
14,
14,
14,
14,
15,
15,
16,
16,
16,
16,
17,
17,
17,
18,
18,
17,
18,
19,
19,
19,
19,
20,
20,
20,
21,
21,
21,
21,
21,
21,
21,
22,
22,
21,
21,
22,
21,
21,
21,
21,
20,
20,
21,
20,
20,
19,
20,
19,
19,
18,
18,
18,
18,
17,
17,
17,
17,
17,
16,
16,
15,
15,
15,
15,
15,
15,
15,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
13,
13,
13,
14,
14,
14,
13,
13,
14,
15,
14,
13,
13,
13,
13,
13,
13,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
15,
15,
15,
15,
15,
15,
15,
16,
16,
16,
16,
16,
17,
17,
17,
17,
18,
19,
19,
19,
19,
20,
20,
20,
21,
21,
21,
21,
22,
21,
21,
21,
21,
21,
21,
21,
22,
22,
22,
22,
21,
21,
21,
21,
21,
21,
20,
20,
19,
19,
19,
18,
18,
17,
17,
17,
17,
16,
16,
16,
16,
15,
16,
15,
14,
15,
15,
14,
14,
14,
14,
14,
13,
13,
13,
14,
14,
14,
14,
14,
13,
13,
14,
13,
13,
13,
13,
13,
13,
12,
12,
12,
13,
14,
13,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
13,
13,
13,
13,
14,
13,
14,
14,
15,
15,
15,
15,
15,
15,
15
] | {
"1. Frame Length": "The total frame length is: 1033.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
9,
9,
8,
9,
9,
9,
9,
10,
10,
10,
10,
10,
11,
11,
11,
11,
11,
11,
12,
12,
12,
12,
13,
13,
13,
13,
13,
14,
14,
14,
14,
15,
15,
15,
15,
15,
15,
15,
16,
16,
16,
16,
17,
16,
16,
16,
17,
17,
17,
17,
17,
17,
16,
16,
17,
17,
16,
17,
17,
16,
16,
16,
16,
16,
16,
16,
15,
15,
15,
15,
15,
15,
15,
14,
13,
14,
14,
13,
13,
13,
13,
13,
13,
13,
12,
12,
13,
12,
12,
13,
12,
12,
12,
12,
12,
12,
12,
12,
12,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
11,
11,
11,
11,
11,
12,
12,
12,
13,
12,
12,
13,
15,
14,
13,
13,
15,
15,
14,
14,
14,
14,
16,
16,
16,
16,
16,
16,
16,
16,
17,
17,
17,
17,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
17,
17,
17,
17,
17,
17,
16,
16,
15,
15,
15,
15,
15,
15,
14,
14,
14,
14,
13,
13,
13,
13,
13,
13,
12,
11,
12,
12,
13,
15,
12,
10,
13,
13,
11,
11,
11,
11,
10,
11,
11,
11,
10,
10,
10,
11,
11,
11,
10,
11,
11,
10,
10,
11,
11,
11,
10,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
12,
12,
12,
12,
12,
12,
12,
12,
13,
13,
13,
13,
13,
13,
13,
14,
14,
14,
14,
14,
14,
15,
15,
16,
16,
16,
16,
16,
17,
17,
17,
18,
18,
18,
18,
18,
19,
19,
19,
19,
18,
18,
18,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
18,
17,
18,
19,
18,
18,
17,
18,
17,
17,
16,
16,
17,
17,
16,
16,
15,
15,
15,
15,
15,
15,
15,
15,
14,
14,
14,
14,
14,
14,
14,
13,
13,
13,
13,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
11,
11,
12,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
10,
10,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
11,
10,
10,
11,
11,
10,
11,
11,
11,
11,
11,
11,
12,
12,
12,
12,
12,
12,
12,
12,
12,
13,
15,
14,
14,
14,
14,
14,
15,
15,
15,
15,
15,
15,
15,
15,
15,
15,
15,
16,
16,
16,
16,
15,
16,
16,
15,
15,
15,
15,
15,
15,
14,
14,
15,
14,
14,
14,
13,
13,
12,
12,
12,
11,
11,
12,
11,
10,
11,
11,
10,
10,
10,
10,
9,
9,
9,
9,
8,
8,
9,
8,
8,
8,
8,
9,
8,
7,
7,
7,
7,
6,
6,
7,
7,
7,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
6,
6,
5,
6,
6,
5,
6,
6,
5,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
6,
7,
8,
7,
7,
7,
7,
7,
8,
8,
8,
9,
8,
7,
7,
8,
8,
8,
8,
8,
8,
8,
9,
8,
8,
9,
9,
8,
8,
9,
9,
9,
10,
8,
9,
9,
9,
9,
9,
9,
9,
9,
8,
7,
8,
9,
9,
8,
8,
8,
9,
8,
7,
7,
8,
7,
7,
7,
7,
6,
5,
6,
7,
6,
5,
6,
5,
5,
4,
4,
4,
5,
4,
4,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
1,
2,
3,
2,
3,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
4,
3,
3,
3,
3,
4,
4,
4,
5,
6,
6,
5,
5,
5,
5,
6,
5,
6,
6,
7,
8,
7,
7,
8,
8,
9,
10,
10,
9,
10,
10,
11,
11,
11,
12,
12,
12,
12,
13,
13,
14,
14,
15,
15,
15,
16,
17,
17,
17,
17,
17,
18,
18,
18,
18,
19,
19,
19,
19,
19,
19,
20,
20,
20,
20,
19,
19,
19,
19,
19,
18,
18,
18,
17,
17,
17,
17,
17,
17,
16,
15,
15,
16,
15,
14,
14,
14,
14,
14,
14,
13,
13,
13,
13,
13,
13,
13,
13,
12,
11,
12,
12,
12,
14,
13,
12,
12,
12,
12,
12,
13,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
13,
13,
12,
12,
13,
13,
13,
13,
13,
13,
14,
13,
13,
14,
14,
14,
14,
14,
15,
15,
16,
16,
16,
16,
17,
17,
17,
18,
18,
17,
18,
19,
19,
19,
19,
20,
20,
20,
21,
21,
21,
21,
21,
21,
21,
22,
22,
21,
21,
22,
21,
21,
21,
21,
20,
20,
21,
20,
20,
19,
20,
19,
19,
18,
18,
18,
18,
17,
17,
17,
17,
17,
16,
16,
15,
15,
15,
15,
15,
15,
15,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
13,
13,
13,
14,
14,
14,
13,
13,
14,
15,
14,
13,
13,
13,
13,
13,
13,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
15,
15,
15,
15,
15,
15,
15,
16,
16,
16,
16,
16,
17,
17,
17,
17,
18,
19,
19,
19,
19,
20,
20,
20,
21,
21,
21,
21,
22,
21,
21,
21,
21,
21,
21,
21,
22,
22,
22,
22,
21,
21,
21,
21,
21,
21,
20,
20,
19,
19,
19,
18,
18,
17,
17,
17,
17,
16,
16,
16,
16,
15,
16,
15,
14,
15,
15,
14,
14,
14,
14,
14,
13,
13,
13,
14,
14,
14,
14,
14,
13,
13,
14,
13,
13,
13,
13,
13,
13,
12,
12,
12,
13,
14,
13,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
13,
13,
13,
13,
14,
13,
14,
14,
15,
15,
15,
15,
15,
15,
15
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
177,
188
],
[
290,
312
],
[
314,
317
],
[
319,
319
],
[
691,
712
],
[
801,
802
],
[
804,
840
],
[
911,
947
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
9,
9,
8,
9,
9,
9,
9,
10,
10,
10,
10,
10,
11,
11,
11,
11,
11,
11,
12,
12,
12,
12,
13,
13,
13,
13,
13,
14,
14,
14,
14,
15,
15,
15,
15,
15,
15,
15,
16,
16,
16,
16,
17,
16,
16,
16,
17,
17,
17,
17,
17,
17,
16,
16,
17,
17,
16,
17,
17,
16,
16,
16,
16,
16,
16,
16,
15,
15,
15,
15,
15,
15,
15,
14,
13,
14,
14,
13,
13,
13,
13,
13,
13,
13,
12,
12,
13,
12,
12,
13,
12,
12,
12,
12,
12,
12,
12,
12,
12,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
11,
11,
11,
11,
11,
12,
12,
12,
13,
12,
12,
13,
15,
14,
13,
13,
15,
15,
14,
14,
14,
14,
16,
16,
16,
16,
16,
16,
16,
16,
17,
17,
17,
17,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
17,
17,
17,
17,
17,
17,
16,
16,
15,
15,
15,
15,
15,
15,
14,
14,
14,
14,
13,
13,
13,
13,
13,
13,
12,
11,
12,
12,
13,
15,
12,
10,
13,
13,
11,
11,
11,
11,
10,
11,
11,
11,
10,
10,
10,
11,
11,
11,
10,
11,
11,
10,
10,
11,
11,
11,
10,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
12,
12,
12,
12,
12,
12,
12,
12,
13,
13,
13,
13,
13,
13,
13,
14,
14,
14,
14,
14,
14,
15,
15,
16,
16,
16,
16,
16,
17,
17,
17,
18,
18,
18,
18,
18,
19,
19,
19,
19,
18,
18,
18,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
18,
17,
18,
19,
18,
18,
17,
18,
17,
17,
16,
16,
17,
17,
16,
16,
15,
15,
15,
15,
15,
15,
15,
15,
14,
14,
14,
14,
14,
14,
14,
13,
13,
13,
13,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
11,
11,
12,
11,
11,
11,
11,
11,
11,
11,
11,
11,
11,
10,
10,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
11,
10,
10,
11,
11,
10,
11,
11,
11,
11,
11,
11,
12,
12,
12,
12,
12,
12,
12,
12,
12,
13,
15,
14,
14,
14,
14,
14,
15,
15,
15,
15,
15,
15,
15,
15,
15,
15,
15,
16,
16,
16,
16,
15,
16,
16,
15,
15,
15,
15,
15,
15,
14,
14,
15,
14,
14,
14,
13,
13,
12,
12,
12,
11,
11,
12,
11,
10,
11,
11,
10,
10,
10,
10,
9,
9,
9,
9,
8,
8,
9,
8,
8,
8,
8,
9,
8,
7,
7,
7,
7,
6,
6,
7,
7,
7,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
6,
6,
5,
6,
6,
5,
6,
6,
5,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
6,
7,
8,
7,
7,
7,
7,
7,
8,
8,
8,
9,
8,
7,
7,
8,
8,
8,
8,
8,
8,
8,
9,
8,
8,
9,
9,
8,
8,
9,
9,
9,
10,
8,
9,
9,
9,
9,
9,
9,
9,
9,
8,
7,
8,
9,
9,
8,
8,
8,
9,
8,
7,
7,
8,
7,
7,
7,
7,
6,
5,
6,
7,
6,
5,
6,
5,
5,
4,
4,
4,
5,
4,
4,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
1,
2,
3,
2,
3,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
4,
3,
3,
3,
3,
4,
4,
4,
5,
6,
6,
5,
5,
5,
5,
6,
5,
6,
6,
7,
8,
7,
7,
8,
8,
9,
10,
10,
9,
10,
10,
11,
11,
11,
12,
12,
12,
12,
13,
13,
14,
14,
15,
15,
15,
16,
17,
17,
17,
17,
17,
18,
18,
18,
18,
19,
19,
19,
19,
19,
19,
20,
20,
20,
20,
19,
19,
19,
19,
19,
18,
18,
18,
17,
17,
17,
17,
17,
17,
16,
15,
15,
16,
15,
14,
14,
14,
14,
14,
14,
13,
13,
13,
13,
13,
13,
13,
13,
12,
11,
12,
12,
12,
14,
13,
12,
12,
12,
12,
12,
13,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
13,
13,
12,
12,
13,
13,
13,
13,
13,
13,
14,
13,
13,
14,
14,
14,
14,
14,
15,
15,
16,
16,
16,
16,
17,
17,
17,
18,
18,
17,
18,
19,
19,
19,
19,
20,
20,
20,
21,
21,
21,
21,
21,
21,
21,
22,
22,
21,
21,
22,
21,
21,
21,
21,
20,
20,
21,
20,
20,
19,
20,
19,
19,
18,
18,
18,
18,
17,
17,
17,
17,
17,
16,
16,
15,
15,
15,
15,
15,
15,
15,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
13,
13,
13,
14,
14,
14,
13,
13,
14,
15,
14,
13,
13,
13,
13,
13,
13,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
15,
15,
15,
15,
15,
15,
15,
16,
16,
16,
16,
16,
17,
17,
17,
17,
18,
19,
19,
19,
19,
20,
20,
20,
21,
21,
21,
21,
22,
21,
21,
21,
21,
21,
21,
21,
22,
22,
22,
22,
21,
21,
21,
21,
21,
21,
20,
20,
19,
19,
19,
18,
18,
17,
17,
17,
17,
16,
16,
16,
16,
15,
16,
15,
14,
15,
15,
14,
14,
14,
14,
14,
13,
13,
13,
14,
14,
14,
14,
14,
13,
13,
14,
13,
13,
13,
13,
13,
13,
12,
12,
12,
13,
14,
13,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
12,
13,
13,
13,
13,
14,
13,
14,
14,
15,
15,
15,
15,
15,
15,
15
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
499,
501
],
[
507,
517
],
[
520,
520
],
[
523,
523
],
[
526,
526
],
[
600,
600
],
[
604,
604
],
[
606,
648
],
[
651,
654
],
[
656,
656
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
2,
2,
2,
1,
1,
1,
2,
2,
1,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
2,
1,
1,
2,
1,
1,
1,
2,
2,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
2,
2,
3,
3,
3,
3,
3,
4,
4,
3,
2,
3,
4,
3,
4,
4,
4,
5,
4,
4,
3,
3,
4,
4,
4,
3,
3,
4,
4,
5,
5,
4,
4,
4,
5,
5,
4,
5,
5,
6,
6,
5,
4,
5,
6,
7,
5,
5,
6,
7,
7,
6,
7,
8,
7,
8,
7,
8,
8,
9,
8,
8,
9,
10,
10,
9,
9,
10,
10,
11,
11,
11,
12,
12,
11,
12,
13,
13,
13,
14,
14,
15,
15,
15,
16,
16,
17,
16,
17,
18,
18,
17,
17,
18,
18,
18,
18,
18,
18,
19,
19,
20,
20,
19,
20,
20,
18,
19,
19,
18,
17,
18,
18,
17,
17,
17,
17,
17,
17,
18,
18,
17,
19,
19,
18,
20,
21,
21,
23,
25,
27,
27,
26,
28,
29,
28,
27,
28,
28,
28,
29,
30,
29,
29,
31,
32,
32,
31,
30,
31,
32,
30,
29,
31,
31,
31,
29,
22,
30,
29,
29,
27,
26,
27,
27,
28,
26,
26,
26,
25,
24,
24,
24,
25,
26,
25,
24,
23,
22,
22,
23,
23,
21,
15,
14,
15,
17,
23,
32,
25,
16,
14,
13,
11,
10,
10,
13,
11,
10,
9,
7,
7,
9,
9,
7,
6,
5,
6,
11,
8,
6,
4,
4,
6,
9,
5,
4,
4,
2,
2,
2,
2,
2,
3,
3,
3,
2,
2,
1,
1,
3,
3,
1,
1,
1,
1,
3,
4,
2,
1,
2,
2,
3,
2,
2,
1,
1,
1,
2,
3,
2,
1,
1,
2,
1,
1,
3,
4,
2,
2,
3,
5,
2,
1,
3,
2,
1,
1,
1,
1,
1,
8,
3,
3,
2,
1,
1,
3,
2,
4,
2,
2,
4,
4,
4,
5,
5,
5,
5,
4,
5,
7,
7,
8,
9,
8,
8,
12,
14,
14,
17,
9,
11,
15,
16,
16,
18,
18,
16,
16,
19,
22,
22,
23,
24,
23,
25,
27,
26,
26,
30,
29,
16,
29,
33,
32,
30,
31,
32,
33,
33,
32,
32,
32,
33,
32,
32,
32,
32,
32,
33,
29,
26,
23,
29,
29,
28,
31,
28,
27,
27,
25,
24,
24,
24,
25,
23,
21,
22,
22,
21,
21,
21,
21,
21,
21,
20,
20,
20,
19,
20,
20,
20,
17,
17,
17,
17,
18,
17,
17,
19,
18,
18,
19,
20,
21,
19,
19,
19,
20,
19,
19,
21,
22,
21,
21,
21,
22,
22,
22
] | {
"1. Frame Length": "The total frame length is: 475.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
2,
2,
2,
1,
1,
1,
2,
2,
1,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
2,
1,
1,
2,
1,
1,
1,
2,
2,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
2,
2,
3,
3,
3,
3,
3,
4,
4,
3,
2,
3,
4,
3,
4,
4,
4,
5,
4,
4,
3,
3,
4,
4,
4,
3,
3,
4,
4,
5,
5,
4,
4,
4,
5,
5,
4,
5,
5,
6,
6,
5,
4,
5,
6,
7,
5,
5,
6,
7,
7,
6,
7,
8,
7,
8,
7,
8,
8,
9,
8,
8,
9,
10,
10,
9,
9,
10,
10,
11,
11,
11,
12,
12,
11,
12,
13,
13,
13,
14,
14,
15,
15,
15,
16,
16,
17,
16,
17,
18,
18,
17,
17,
18,
18,
18,
18,
18,
18,
19,
19,
20,
20,
19,
20,
20,
18,
19,
19,
18,
17,
18,
18,
17,
17,
17,
17,
17,
17,
18,
18,
17,
19,
19,
18,
20,
21,
21,
23,
25,
27,
27,
26,
28,
29,
28,
27,
28,
28,
28,
29,
30,
29,
29,
31,
32,
32,
31,
30,
31,
32,
30,
29,
31,
31,
31,
29,
22,
30,
29,
29,
27,
26,
27,
27,
28,
26,
26,
26,
25,
24,
24,
24,
25,
26,
25,
24,
23,
22,
22,
23,
23,
21,
15,
14,
15,
17,
23,
32,
25,
16,
14,
13,
11,
10,
10,
13,
11,
10,
9,
7,
7,
9,
9,
7,
6,
5,
6,
11,
8,
6,
4,
4,
6,
9,
5,
4,
4,
2,
2,
2,
2,
2,
3,
3,
3,
2,
2,
1,
1,
3,
3,
1,
1,
1,
1,
3,
4,
2,
1,
2,
2,
3,
2,
2,
1,
1,
1,
2,
3,
2,
1,
1,
2,
1,
1,
3,
4,
2,
2,
3,
5,
2,
1,
3,
2,
1,
1,
1,
1,
1,
8,
3,
3,
2,
1,
1,
3,
2,
4,
2,
2,
4,
4,
4,
5,
5,
5,
5,
4,
5,
7,
7,
8,
9,
8,
8,
12,
14,
14,
17,
9,
11,
15,
16,
16,
18,
18,
16,
16,
19,
22,
22,
23,
24,
23,
25,
27,
26,
26,
30,
29,
16,
29,
33,
32,
30,
31,
32,
33,
33,
32,
32,
32,
33,
32,
32,
32,
32,
32,
33,
29,
26,
23,
29,
29,
28,
31,
28,
27,
27,
25,
24,
24,
24,
25,
23,
21,
22,
22,
21,
21,
21,
21,
21,
21,
20,
20,
20,
19,
20,
20,
20,
17,
17,
17,
17,
18,
17,
17,
19,
18,
18,
19,
20,
21,
19,
19,
19,
20,
19,
19,
21,
22,
21,
21,
21,
22,
22,
22
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
205,
206
],
[
208,
231
],
[
233,
236
],
[
238,
240
],
[
263,
263
],
[
392,
392
],
[
395,
396
],
[
398,
416
],
[
419,
425
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
2,
2,
2,
1,
1,
1,
2,
2,
1,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
2,
1,
1,
2,
1,
1,
1,
2,
2,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
2,
2,
3,
3,
3,
3,
3,
4,
4,
3,
2,
3,
4,
3,
4,
4,
4,
5,
4,
4,
3,
3,
4,
4,
4,
3,
3,
4,
4,
5,
5,
4,
4,
4,
5,
5,
4,
5,
5,
6,
6,
5,
4,
5,
6,
7,
5,
5,
6,
7,
7,
6,
7,
8,
7,
8,
7,
8,
8,
9,
8,
8,
9,
10,
10,
9,
9,
10,
10,
11,
11,
11,
12,
12,
11,
12,
13,
13,
13,
14,
14,
15,
15,
15,
16,
16,
17,
16,
17,
18,
18,
17,
17,
18,
18,
18,
18,
18,
18,
19,
19,
20,
20,
19,
20,
20,
18,
19,
19,
18,
17,
18,
18,
17,
17,
17,
17,
17,
17,
18,
18,
17,
19,
19,
18,
20,
21,
21,
23,
25,
27,
27,
26,
28,
29,
28,
27,
28,
28,
28,
29,
30,
29,
29,
31,
32,
32,
31,
30,
31,
32,
30,
29,
31,
31,
31,
29,
22,
30,
29,
29,
27,
26,
27,
27,
28,
26,
26,
26,
25,
24,
24,
24,
25,
26,
25,
24,
23,
22,
22,
23,
23,
21,
15,
14,
15,
17,
23,
32,
25,
16,
14,
13,
11,
10,
10,
13,
11,
10,
9,
7,
7,
9,
9,
7,
6,
5,
6,
11,
8,
6,
4,
4,
6,
9,
5,
4,
4,
2,
2,
2,
2,
2,
3,
3,
3,
2,
2,
1,
1,
3,
3,
1,
1,
1,
1,
3,
4,
2,
1,
2,
2,
3,
2,
2,
1,
1,
1,
2,
3,
2,
1,
1,
2,
1,
1,
3,
4,
2,
2,
3,
5,
2,
1,
3,
2,
1,
1,
1,
1,
1,
8,
3,
3,
2,
1,
1,
3,
2,
4,
2,
2,
4,
4,
4,
5,
5,
5,
5,
4,
5,
7,
7,
8,
9,
8,
8,
12,
14,
14,
17,
9,
11,
15,
16,
16,
18,
18,
16,
16,
19,
22,
22,
23,
24,
23,
25,
27,
26,
26,
30,
29,
16,
29,
33,
32,
30,
31,
32,
33,
33,
32,
32,
32,
33,
32,
32,
32,
32,
32,
33,
29,
26,
23,
29,
29,
28,
31,
28,
27,
27,
25,
24,
24,
24,
25,
23,
21,
22,
22,
21,
21,
21,
21,
21,
21,
20,
20,
20,
19,
20,
20,
20,
17,
17,
17,
17,
18,
17,
17,
19,
18,
18,
19,
20,
21,
19,
19,
19,
20,
19,
19,
21,
22,
21,
21,
21,
22,
22,
22
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
127
],
[
129,
129
],
[
131,
131
],
[
275,
276
],
[
279,
282
],
[
285,
288
],
[
290,
345
],
[
347,
367
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
0,
1,
1,
0,
0,
1,
1,
1,
1,
2,
2,
3,
3,
2,
2,
2,
3,
3,
3,
3,
3,
2,
2,
3,
2,
2,
3,
3,
2,
4,
5,
5,
3,
5,
6,
4,
3,
4,
6,
6,
7,
7,
7,
8,
10,
9,
9,
8,
7,
6,
7,
8,
10,
10,
11,
10,
10,
9,
9,
11,
12,
11,
12,
12,
11,
11,
11,
11,
11,
11,
11,
10,
11,
11,
10,
11,
11,
11,
11,
10,
10,
9,
9,
10,
10,
9,
9,
10,
9,
9,
9,
8,
7,
8,
8,
7,
7,
6,
7,
7,
6,
7,
5,
6,
6,
5,
5,
4,
3,
3,
3,
3,
3,
2,
2,
2,
2,
1,
1,
2,
2,
2,
2,
3,
4,
3,
2,
4,
4,
4,
6,
6,
6,
6,
6,
6,
7,
8,
8,
8,
8,
9,
10,
10,
10,
11,
12,
12,
12,
14,
14,
13,
14,
15,
14,
17,
17,
17,
17,
17,
17,
19,
20,
19,
20,
20,
20,
20,
20,
21,
20,
20,
19,
19,
19,
18,
17,
17,
17,
16,
15,
13,
12,
12,
11,
9,
9,
7,
3,
2,
1,
4,
4,
4,
5,
6,
7,
8,
9,
11,
12,
14,
15,
15,
16,
16,
15,
14,
14,
15,
16,
18,
22,
17,
17,
16,
17,
18,
18,
18,
18,
18,
18,
19,
18,
17,
17,
17,
17,
16,
15,
16,
16,
15,
13,
13,
12,
11,
10,
9,
10,
9,
8,
7,
7,
7,
6,
5,
5,
5,
4,
3,
3,
3,
2,
2,
2,
2,
2,
1,
1,
0,
1,
1,
1,
2,
2,
1,
2,
2,
2,
2,
3,
3,
3,
4,
4,
3,
3,
3,
3,
2,
3,
4,
4,
2,
3,
3,
3,
3,
4,
3,
3,
2,
3,
4,
3,
4,
3,
3,
3,
3,
4,
4,
3,
3,
4,
3,
2,
3,
4,
4,
3
] | {
"1. Frame Length": "The total frame length is: 364.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
0,
1,
1,
0,
0,
1,
1,
1,
1,
2,
2,
3,
3,
2,
2,
2,
3,
3,
3,
3,
3,
2,
2,
3,
2,
2,
3,
3,
2,
4,
5,
5,
3,
5,
6,
4,
3,
4,
6,
6,
7,
7,
7,
8,
10,
9,
9,
8,
7,
6,
7,
8,
10,
10,
11,
10,
10,
9,
9,
11,
12,
11,
12,
12,
11,
11,
11,
11,
11,
11,
11,
10,
11,
11,
10,
11,
11,
11,
11,
10,
10,
9,
9,
10,
10,
9,
9,
10,
9,
9,
9,
8,
7,
8,
8,
7,
7,
6,
7,
7,
6,
7,
5,
6,
6,
5,
5,
4,
3,
3,
3,
3,
3,
2,
2,
2,
2,
1,
1,
2,
2,
2,
2,
3,
4,
3,
2,
4,
4,
4,
6,
6,
6,
6,
6,
6,
7,
8,
8,
8,
8,
9,
10,
10,
10,
11,
12,
12,
12,
14,
14,
13,
14,
15,
14,
17,
17,
17,
17,
17,
17,
19,
20,
19,
20,
20,
20,
20,
20,
21,
20,
20,
19,
19,
19,
18,
17,
17,
17,
16,
15,
13,
12,
12,
11,
9,
9,
7,
3,
2,
1,
4,
4,
4,
5,
6,
7,
8,
9,
11,
12,
14,
15,
15,
16,
16,
15,
14,
14,
15,
16,
18,
22,
17,
17,
16,
17,
18,
18,
18,
18,
18,
18,
19,
18,
17,
17,
17,
17,
16,
15,
16,
16,
15,
13,
13,
12,
11,
10,
9,
10,
9,
8,
7,
7,
7,
6,
5,
5,
5,
4,
3,
3,
3,
2,
2,
2,
2,
2,
1,
1,
0,
1,
1,
1,
2,
2,
1,
2,
2,
2,
2,
3,
3,
3,
4,
4,
3,
3,
3,
3,
2,
3,
4,
4,
2,
3,
3,
3,
3,
4,
3,
3,
2,
3,
4,
3,
4,
3,
3,
3,
3,
4,
4,
3,
3,
4,
3,
2,
3,
4,
4,
3
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
212,
226
],
[
262,
263
],
[
268,
275
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
0,
1,
1,
0,
0,
1,
1,
1,
1,
2,
2,
3,
3,
2,
2,
2,
3,
3,
3,
3,
3,
2,
2,
3,
2,
2,
3,
3,
2,
4,
5,
5,
3,
5,
6,
4,
3,
4,
6,
6,
7,
7,
7,
8,
10,
9,
9,
8,
7,
6,
7,
8,
10,
10,
11,
10,
10,
9,
9,
11,
12,
11,
12,
12,
11,
11,
11,
11,
11,
11,
11,
10,
11,
11,
10,
11,
11,
11,
11,
10,
10,
9,
9,
10,
10,
9,
9,
10,
9,
9,
9,
8,
7,
8,
8,
7,
7,
6,
7,
7,
6,
7,
5,
6,
6,
5,
5,
4,
3,
3,
3,
3,
3,
2,
2,
2,
2,
1,
1,
2,
2,
2,
2,
3,
4,
3,
2,
4,
4,
4,
6,
6,
6,
6,
6,
6,
7,
8,
8,
8,
8,
9,
10,
10,
10,
11,
12,
12,
12,
14,
14,
13,
14,
15,
14,
17,
17,
17,
17,
17,
17,
19,
20,
19,
20,
20,
20,
20,
20,
21,
20,
20,
19,
19,
19,
18,
17,
17,
17,
16,
15,
13,
12,
12,
11,
9,
9,
7,
3,
2,
1,
4,
4,
4,
5,
6,
7,
8,
9,
11,
12,
14,
15,
15,
16,
16,
15,
14,
14,
15,
16,
18,
22,
17,
17,
16,
17,
18,
18,
18,
18,
18,
18,
19,
18,
17,
17,
17,
17,
16,
15,
16,
16,
15,
13,
13,
12,
11,
10,
9,
10,
9,
8,
7,
7,
7,
6,
5,
5,
5,
4,
3,
3,
3,
2,
2,
2,
2,
2,
1,
1,
0,
1,
1,
1,
2,
2,
1,
2,
2,
2,
2,
3,
3,
3,
4,
4,
3,
3,
3,
3,
2,
3,
4,
4,
2,
3,
3,
3,
3,
4,
3,
3,
2,
3,
4,
3,
4,
3,
3,
3,
3,
4,
4,
3,
3,
4,
3,
2,
3,
4,
4,
3
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
80
],
[
83,
83
],
[
86,
88
],
[
158,
180
],
[
239,
244
],
[
301,
363
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
1,
1,
1,
0,
1,
1,
0,
0,
0,
0,
1,
1,
1,
0,
0,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
2,
2,
2,
1,
1,
3,
4,
3,
3,
3,
4,
4,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
3,
4,
4,
4,
6,
8,
9,
11,
11,
10,
9,
7,
6,
5,
5,
5,
5,
6,
7,
5,
7,
7,
7,
6,
5,
4,
4,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
4,
4,
3,
3,
3,
4,
7,
9,
11,
12,
12,
11,
11,
10,
9,
8,
7,
5,
2,
4,
6,
8,
8,
9,
9,
9,
9,
9,
8,
7,
5,
5,
4,
3,
2,
3,
3,
3,
3,
2,
3,
6,
9,
11,
12,
13,
13,
15,
16,
12,
9,
3,
2,
4,
6,
7,
7,
8,
9,
10,
11,
11,
12,
13,
11,
9,
8,
9,
11,
7,
6,
5,
4,
5,
5,
4,
3,
3,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
4,
2,
1,
2,
3,
3,
2,
2,
3,
3,
5,
6,
7,
9,
13,
15,
16,
19,
20,
21,
21,
20,
18,
15,
12,
9,
7,
13,
17,
21,
24,
27,
28,
26,
24,
23,
22,
21,
20,
19,
19,
20,
20,
20,
17,
13,
9,
11,
8,
9,
8,
9,
9,
8,
7,
7,
6,
6,
6,
5,
5,
5,
2,
4,
10,
7,
4,
5,
5,
5,
5,
6,
2,
3,
4,
4,
4,
3,
3,
3,
5,
4,
4,
4,
5,
1,
2,
2,
2,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
3,
3,
3,
4,
3,
3,
3,
4,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
5,
4,
4,
5,
4,
4,
4,
4,
4,
3,
3,
3,
3,
2,
3,
3,
2,
2,
2,
1,
1,
2,
1,
2,
3,
2,
2,
2,
2,
2,
2,
1,
2,
2,
1,
2,
2,
3,
3,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
4
] | {
"1. Frame Length": "The total frame length is: 442.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
1,
1,
1,
0,
1,
1,
0,
0,
0,
0,
1,
1,
1,
0,
0,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
2,
2,
2,
1,
1,
3,
4,
3,
3,
3,
4,
4,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
3,
4,
4,
4,
6,
8,
9,
11,
11,
10,
9,
7,
6,
5,
5,
5,
5,
6,
7,
5,
7,
7,
7,
6,
5,
4,
4,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
4,
4,
3,
3,
3,
4,
7,
9,
11,
12,
12,
11,
11,
10,
9,
8,
7,
5,
2,
4,
6,
8,
8,
9,
9,
9,
9,
9,
8,
7,
5,
5,
4,
3,
2,
3,
3,
3,
3,
2,
3,
6,
9,
11,
12,
13,
13,
15,
16,
12,
9,
3,
2,
4,
6,
7,
7,
8,
9,
10,
11,
11,
12,
13,
11,
9,
8,
9,
11,
7,
6,
5,
4,
5,
5,
4,
3,
3,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
4,
2,
1,
2,
3,
3,
2,
2,
3,
3,
5,
6,
7,
9,
13,
15,
16,
19,
20,
21,
21,
20,
18,
15,
12,
9,
7,
13,
17,
21,
24,
27,
28,
26,
24,
23,
22,
21,
20,
19,
19,
20,
20,
20,
17,
13,
9,
11,
8,
9,
8,
9,
9,
8,
7,
7,
6,
6,
6,
5,
5,
5,
2,
4,
10,
7,
4,
5,
5,
5,
5,
6,
2,
3,
4,
4,
4,
3,
3,
3,
5,
4,
4,
4,
5,
1,
2,
2,
2,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
3,
3,
3,
4,
3,
3,
3,
4,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
5,
4,
4,
5,
4,
4,
4,
4,
4,
3,
3,
3,
3,
2,
3,
3,
2,
2,
2,
1,
1,
2,
1,
2,
3,
2,
2,
2,
2,
2,
2,
1,
2,
2,
1,
2,
2,
3,
3,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
4
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
304,
309
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
1,
1,
1,
0,
1,
1,
0,
0,
0,
0,
1,
1,
1,
0,
0,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
2,
2,
2,
1,
1,
3,
4,
3,
3,
3,
4,
4,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
3,
4,
4,
4,
6,
8,
9,
11,
11,
10,
9,
7,
6,
5,
5,
5,
5,
6,
7,
5,
7,
7,
7,
6,
5,
4,
4,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
4,
4,
3,
3,
3,
4,
7,
9,
11,
12,
12,
11,
11,
10,
9,
8,
7,
5,
2,
4,
6,
8,
8,
9,
9,
9,
9,
9,
8,
7,
5,
5,
4,
3,
2,
3,
3,
3,
3,
2,
3,
6,
9,
11,
12,
13,
13,
15,
16,
12,
9,
3,
2,
4,
6,
7,
7,
8,
9,
10,
11,
11,
12,
13,
11,
9,
8,
9,
11,
7,
6,
5,
4,
5,
5,
4,
3,
3,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
4,
2,
1,
2,
3,
3,
2,
2,
3,
3,
5,
6,
7,
9,
13,
15,
16,
19,
20,
21,
21,
20,
18,
15,
12,
9,
7,
13,
17,
21,
24,
27,
28,
26,
24,
23,
22,
21,
20,
19,
19,
20,
20,
20,
17,
13,
9,
11,
8,
9,
8,
9,
9,
8,
7,
7,
6,
6,
6,
5,
5,
5,
2,
4,
10,
7,
4,
5,
5,
5,
5,
6,
2,
3,
4,
4,
4,
3,
3,
3,
5,
4,
4,
4,
5,
1,
2,
2,
2,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
3,
3,
3,
4,
3,
3,
3,
4,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
5,
4,
4,
5,
4,
4,
4,
4,
4,
3,
3,
3,
3,
2,
3,
3,
2,
2,
2,
1,
1,
2,
1,
2,
3,
2,
2,
2,
2,
2,
2,
1,
2,
2,
1,
2,
2,
3,
3,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
4
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
151
],
[
161,
164
],
[
167,
167
],
[
172,
190
],
[
202,
204
],
[
215,
225
],
[
236,
238
],
[
256,
284
],
[
333,
337
],
[
340,
344
],
[
346,
441
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
1,
1,
0,
0,
1,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
1,
1,
0,
1,
1,
1,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
1,
1,
0,
1,
1,
0,
1,
0,
1,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
1,
0,
0,
1,
1,
1,
0,
1,
2,
1,
1,
1,
1,
0,
1,
0,
1,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
1,
2,
2,
2,
2,
2,
2,
1,
1,
2,
2,
2,
3,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
2,
2,
2,
2,
3,
3,
4,
5,
6,
7,
9,
11,
12,
15,
17,
19,
21,
23,
26,
27,
28,
30,
30,
31,
32,
32,
32,
32,
31,
31,
32,
32,
30,
26,
23,
21,
20,
17,
15,
10,
8,
5,
6,
8,
12,
15,
21,
26,
31,
38,
44,
46,
55,
61,
68,
74,
78,
82,
86,
87,
87,
87,
85,
82,
79,
74,
69,
65,
65,
60,
59,
52,
51,
48,
37,
43,
40,
34,
31,
35,
34,
33,
32,
26,
24,
22,
21,
18,
14,
13,
13,
12,
11,
15,
16,
16,
17,
20,
22,
25,
26,
27,
31,
35,
37,
40,
43,
45,
48,
50,
51,
47,
57,
60,
62,
65,
69,
71,
72,
74,
77,
79,
80,
77,
72,
72,
66,
57,
53,
50,
38,
34,
29,
22,
19,
21,
21,
21,
19,
19,
14,
9,
5,
7,
7,
5,
7,
7,
6,
7,
7,
10,
12,
13,
14,
15,
16,
17,
15,
14,
13,
13,
13,
14,
13,
13,
14,
13,
11,
10,
9,
9,
8,
7,
7,
7,
6,
5,
5,
4,
4,
3,
3,
2,
3,
3,
3,
3,
4,
5,
3,
3,
3,
3,
3,
3,
2,
1,
1,
1,
1,
1,
2,
2,
1,
1,
2,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
3,
3,
2,
3,
4,
4,
4,
4,
5,
5,
5,
6,
5,
6,
6,
6,
7,
7,
7,
7,
7,
8,
8,
8,
9,
9,
9,
9,
9,
9,
9,
9,
9,
11,
9,
9,
11,
10,
10,
8,
10,
9,
10,
9,
9,
9,
9,
9,
8,
8,
10,
8,
8,
7,
8,
9,
8,
8,
7,
7,
7,
7,
7,
7,
6,
5,
6,
6,
5,
5,
6,
6,
5,
4,
6,
6,
5,
4,
3,
4,
4,
4,
4,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
2,
2,
1,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
1,
1,
1,
1,
0,
1,
0,
0,
1,
1,
0,
0,
1,
1,
2,
2,
1,
1,
1
] | {
"1. Frame Length": "The total frame length is: 503.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
1,
1,
0,
0,
1,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
1,
1,
0,
1,
1,
1,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
1,
1,
0,
1,
1,
0,
1,
0,
1,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
1,
0,
0,
1,
1,
1,
0,
1,
2,
1,
1,
1,
1,
0,
1,
0,
1,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
1,
2,
2,
2,
2,
2,
2,
1,
1,
2,
2,
2,
3,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
2,
2,
2,
2,
3,
3,
4,
5,
6,
7,
9,
11,
12,
15,
17,
19,
21,
23,
26,
27,
28,
30,
30,
31,
32,
32,
32,
32,
31,
31,
32,
32,
30,
26,
23,
21,
20,
17,
15,
10,
8,
5,
6,
8,
12,
15,
21,
26,
31,
38,
44,
46,
55,
61,
68,
74,
78,
82,
86,
87,
87,
87,
85,
82,
79,
74,
69,
65,
65,
60,
59,
52,
51,
48,
37,
43,
40,
34,
31,
35,
34,
33,
32,
26,
24,
22,
21,
18,
14,
13,
13,
12,
11,
15,
16,
16,
17,
20,
22,
25,
26,
27,
31,
35,
37,
40,
43,
45,
48,
50,
51,
47,
57,
60,
62,
65,
69,
71,
72,
74,
77,
79,
80,
77,
72,
72,
66,
57,
53,
50,
38,
34,
29,
22,
19,
21,
21,
21,
19,
19,
14,
9,
5,
7,
7,
5,
7,
7,
6,
7,
7,
10,
12,
13,
14,
15,
16,
17,
15,
14,
13,
13,
13,
14,
13,
13,
14,
13,
11,
10,
9,
9,
8,
7,
7,
7,
6,
5,
5,
4,
4,
3,
3,
2,
3,
3,
3,
3,
4,
5,
3,
3,
3,
3,
3,
3,
2,
1,
1,
1,
1,
1,
2,
2,
1,
1,
2,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
3,
3,
2,
3,
4,
4,
4,
4,
5,
5,
5,
6,
5,
6,
6,
6,
7,
7,
7,
7,
7,
8,
8,
8,
9,
9,
9,
9,
9,
9,
9,
9,
9,
11,
9,
9,
11,
10,
10,
8,
10,
9,
10,
9,
9,
9,
9,
9,
8,
8,
10,
8,
8,
7,
8,
9,
8,
8,
7,
7,
7,
7,
7,
7,
6,
5,
6,
6,
5,
5,
6,
6,
5,
4,
6,
6,
5,
4,
3,
4,
4,
4,
4,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
2,
2,
1,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
1,
1,
1,
1,
0,
1,
0,
0,
1,
1,
0,
0,
1,
1,
2,
2,
1,
1,
1
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
210,
220
],
[
272,
280
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
1,
1,
0,
0,
1,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
1,
1,
0,
1,
1,
1,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
1,
1,
0,
1,
1,
0,
1,
0,
1,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
1,
0,
0,
1,
1,
1,
0,
1,
2,
1,
1,
1,
1,
0,
1,
0,
1,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
1,
2,
2,
2,
2,
2,
2,
1,
1,
2,
2,
2,
3,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
2,
2,
2,
2,
3,
3,
4,
5,
6,
7,
9,
11,
12,
15,
17,
19,
21,
23,
26,
27,
28,
30,
30,
31,
32,
32,
32,
32,
31,
31,
32,
32,
30,
26,
23,
21,
20,
17,
15,
10,
8,
5,
6,
8,
12,
15,
21,
26,
31,
38,
44,
46,
55,
61,
68,
74,
78,
82,
86,
87,
87,
87,
85,
82,
79,
74,
69,
65,
65,
60,
59,
52,
51,
48,
37,
43,
40,
34,
31,
35,
34,
33,
32,
26,
24,
22,
21,
18,
14,
13,
13,
12,
11,
15,
16,
16,
17,
20,
22,
25,
26,
27,
31,
35,
37,
40,
43,
45,
48,
50,
51,
47,
57,
60,
62,
65,
69,
71,
72,
74,
77,
79,
80,
77,
72,
72,
66,
57,
53,
50,
38,
34,
29,
22,
19,
21,
21,
21,
19,
19,
14,
9,
5,
7,
7,
5,
7,
7,
6,
7,
7,
10,
12,
13,
14,
15,
16,
17,
15,
14,
13,
13,
13,
14,
13,
13,
14,
13,
11,
10,
9,
9,
8,
7,
7,
7,
6,
5,
5,
4,
4,
3,
3,
2,
3,
3,
3,
3,
4,
5,
3,
3,
3,
3,
3,
3,
2,
1,
1,
1,
1,
1,
2,
2,
1,
1,
2,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
3,
3,
2,
3,
4,
4,
4,
4,
5,
5,
5,
6,
5,
6,
6,
6,
7,
7,
7,
7,
7,
8,
8,
8,
9,
9,
9,
9,
9,
9,
9,
9,
9,
11,
9,
9,
11,
10,
10,
8,
10,
9,
10,
9,
9,
9,
9,
9,
8,
8,
10,
8,
8,
7,
8,
9,
8,
8,
7,
7,
7,
7,
7,
7,
6,
5,
6,
6,
5,
5,
6,
6,
5,
4,
6,
6,
5,
4,
3,
4,
4,
4,
4,
3,
3,
3,
4,
3,
3,
3,
3,
3,
3,
2,
2,
1,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
1,
1,
1,
1,
0,
1,
0,
0,
1,
1,
0,
0,
1,
1,
2,
2,
1,
1,
1
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
169
],
[
192,
200
],
[
243,
251
],
[
295,
502
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
5,
5,
3,
1,
1,
4,
0,
0,
0,
0,
1,
1,
0,
0,
1,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
0,
0,
0,
0,
0,
0,
1,
1,
0,
1,
1,
1,
0,
0,
0,
0,
0,
1,
1,
1,
0,
0,
1,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
2,
2,
1,
1,
1,
1,
1,
1,
2,
2,
1,
0,
1,
1,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
5,
4,
4,
4,
5,
5,
5,
5,
6,
4,
6,
5,
6,
6,
6,
6,
6,
6,
6,
5,
6,
7,
6,
6,
6,
6,
6,
5,
5,
4,
4,
3,
4,
4,
4,
3,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
4,
3,
5,
5,
4,
4,
5,
6,
6,
5,
6,
6,
6,
6,
7,
7,
7,
7,
8,
9,
8,
8,
8,
9,
9,
9,
10,
9,
10,
11,
13,
11,
11,
12,
12,
12,
13,
13,
13,
13,
14,
15,
14,
14,
16,
16,
16,
16,
16,
14,
21,
18,
19,
19,
20,
19,
18,
19,
21,
21,
22,
22,
23,
24,
24,
25,
26,
25,
26,
27,
27,
28,
29,
29,
35,
27,
31,
31,
32,
33,
33,
34,
35,
35,
35,
36,
37,
38,
39,
39,
38,
39,
39,
41,
43,
36,
40,
40,
38,
41,
42,
42,
43,
43,
45,
46,
46,
46,
45,
44,
45,
44,
44,
44,
43,
43,
43,
44,
43,
43,
43,
43,
43,
44,
44,
43,
42,
42,
41,
39,
40,
39,
40,
39,
36,
37,
36,
36,
37,
36,
36,
35,
35,
33,
34,
33,
34,
33,
30,
31,
30,
32,
30,
32,
31,
33,
29,
31,
31,
30,
30,
30,
29,
29,
30,
30,
32,
30,
31,
31,
31,
30,
32,
32,
32,
33,
34,
34,
33,
33,
34,
35,
34,
34,
34,
36,
36,
36,
37,
37,
39,
40,
40,
40,
40,
42,
43,
42,
44,
44,
44,
42,
41,
41,
40,
40,
40,
42,
42,
40,
43,
43,
43,
44,
43,
41,
41,
40,
41,
40,
40,
39,
43,
41,
42,
41,
40,
41,
41,
41,
41,
39,
38,
38,
36,
34,
38,
37,
33,
34,
33,
33,
33,
33,
32,
31,
31,
30,
29,
29,
28,
27,
27,
27,
27,
23,
25,
24,
24,
23,
22,
22,
21,
21,
20,
19,
18,
18,
20,
18,
18,
17,
16,
16,
15,
14,
15,
15,
14,
14,
14,
13,
12,
12,
12,
11,
11,
11,
11,
10,
10,
9,
9,
9,
9,
7,
8,
7,
7,
7,
6,
6,
6,
6,
5,
5,
5,
4,
4,
3,
3,
3,
3,
2,
3,
3,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
2,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
3,
3,
2,
2,
3,
3,
2,
2,
2,
1,
3,
3,
2,
2,
2,
2,
2,
3,
2,
2,
3,
2,
2,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
4,
4,
5,
4,
4,
4,
5,
5,
3,
4,
4,
4,
5,
4,
5,
4,
3,
4,
5,
4,
3,
3,
4,
4,
4,
2,
4,
5,
3,
4,
3,
4,
2,
3,
2,
2,
2,
3,
4,
3,
3,
2,
2,
3,
3,
2,
2,
2,
1,
2,
2,
1,
1,
2,
2,
1,
1,
1,
1,
2,
1,
1,
0,
0,
1,
1,
1,
1,
1,
0,
0,
1,
0,
0,
0,
0,
1,
0,
0,
1,
1,
0,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
1,
1,
1,
0,
0,
0,
1,
1,
1,
2,
1,
1,
1,
0,
2,
1,
2,
7,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
1,
1,
0,
0,
0,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
2
] | {
"1. Frame Length": "The total frame length is: 884.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
5,
5,
3,
1,
1,
4,
0,
0,
0,
0,
1,
1,
0,
0,
1,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
0,
0,
0,
0,
0,
0,
1,
1,
0,
1,
1,
1,
0,
0,
0,
0,
0,
1,
1,
1,
0,
0,
1,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
2,
2,
1,
1,
1,
1,
1,
1,
2,
2,
1,
0,
1,
1,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
5,
4,
4,
4,
5,
5,
5,
5,
6,
4,
6,
5,
6,
6,
6,
6,
6,
6,
6,
5,
6,
7,
6,
6,
6,
6,
6,
5,
5,
4,
4,
3,
4,
4,
4,
3,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
4,
3,
5,
5,
4,
4,
5,
6,
6,
5,
6,
6,
6,
6,
7,
7,
7,
7,
8,
9,
8,
8,
8,
9,
9,
9,
10,
9,
10,
11,
13,
11,
11,
12,
12,
12,
13,
13,
13,
13,
14,
15,
14,
14,
16,
16,
16,
16,
16,
14,
21,
18,
19,
19,
20,
19,
18,
19,
21,
21,
22,
22,
23,
24,
24,
25,
26,
25,
26,
27,
27,
28,
29,
29,
35,
27,
31,
31,
32,
33,
33,
34,
35,
35,
35,
36,
37,
38,
39,
39,
38,
39,
39,
41,
43,
36,
40,
40,
38,
41,
42,
42,
43,
43,
45,
46,
46,
46,
45,
44,
45,
44,
44,
44,
43,
43,
43,
44,
43,
43,
43,
43,
43,
44,
44,
43,
42,
42,
41,
39,
40,
39,
40,
39,
36,
37,
36,
36,
37,
36,
36,
35,
35,
33,
34,
33,
34,
33,
30,
31,
30,
32,
30,
32,
31,
33,
29,
31,
31,
30,
30,
30,
29,
29,
30,
30,
32,
30,
31,
31,
31,
30,
32,
32,
32,
33,
34,
34,
33,
33,
34,
35,
34,
34,
34,
36,
36,
36,
37,
37,
39,
40,
40,
40,
40,
42,
43,
42,
44,
44,
44,
42,
41,
41,
40,
40,
40,
42,
42,
40,
43,
43,
43,
44,
43,
41,
41,
40,
41,
40,
40,
39,
43,
41,
42,
41,
40,
41,
41,
41,
41,
39,
38,
38,
36,
34,
38,
37,
33,
34,
33,
33,
33,
33,
32,
31,
31,
30,
29,
29,
28,
27,
27,
27,
27,
23,
25,
24,
24,
23,
22,
22,
21,
21,
20,
19,
18,
18,
20,
18,
18,
17,
16,
16,
15,
14,
15,
15,
14,
14,
14,
13,
12,
12,
12,
11,
11,
11,
11,
10,
10,
9,
9,
9,
9,
7,
8,
7,
7,
7,
6,
6,
6,
6,
5,
5,
5,
4,
4,
3,
3,
3,
3,
2,
3,
3,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
2,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
3,
3,
2,
2,
3,
3,
2,
2,
2,
1,
3,
3,
2,
2,
2,
2,
2,
3,
2,
2,
3,
2,
2,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
4,
4,
5,
4,
4,
4,
5,
5,
3,
4,
4,
4,
5,
4,
5,
4,
3,
4,
5,
4,
3,
3,
4,
4,
4,
2,
4,
5,
3,
4,
3,
4,
2,
3,
2,
2,
2,
3,
4,
3,
3,
2,
2,
3,
3,
2,
2,
2,
1,
2,
2,
1,
1,
2,
2,
1,
1,
1,
1,
2,
1,
1,
0,
0,
1,
1,
1,
1,
1,
0,
0,
1,
0,
0,
0,
0,
1,
0,
0,
1,
1,
0,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
1,
1,
1,
0,
0,
0,
1,
1,
1,
2,
1,
1,
1,
0,
2,
1,
2,
7,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
1,
1,
0,
0,
0,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
2
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
398,
406
],
[
408,
445
],
[
447,
447
],
[
450,
450
],
[
500,
545
],
[
548,
549
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
5,
5,
3,
1,
1,
4,
0,
0,
0,
0,
1,
1,
0,
0,
1,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
0,
0,
0,
0,
0,
0,
1,
1,
0,
1,
1,
1,
0,
0,
0,
0,
0,
1,
1,
1,
0,
0,
1,
0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
2,
2,
1,
1,
1,
1,
1,
1,
2,
2,
1,
0,
1,
1,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
5,
4,
4,
4,
5,
5,
5,
5,
6,
4,
6,
5,
6,
6,
6,
6,
6,
6,
6,
5,
6,
7,
6,
6,
6,
6,
6,
5,
5,
4,
4,
3,
4,
4,
4,
3,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
4,
3,
5,
5,
4,
4,
5,
6,
6,
5,
6,
6,
6,
6,
7,
7,
7,
7,
8,
9,
8,
8,
8,
9,
9,
9,
10,
9,
10,
11,
13,
11,
11,
12,
12,
12,
13,
13,
13,
13,
14,
15,
14,
14,
16,
16,
16,
16,
16,
14,
21,
18,
19,
19,
20,
19,
18,
19,
21,
21,
22,
22,
23,
24,
24,
25,
26,
25,
26,
27,
27,
28,
29,
29,
35,
27,
31,
31,
32,
33,
33,
34,
35,
35,
35,
36,
37,
38,
39,
39,
38,
39,
39,
41,
43,
36,
40,
40,
38,
41,
42,
42,
43,
43,
45,
46,
46,
46,
45,
44,
45,
44,
44,
44,
43,
43,
43,
44,
43,
43,
43,
43,
43,
44,
44,
43,
42,
42,
41,
39,
40,
39,
40,
39,
36,
37,
36,
36,
37,
36,
36,
35,
35,
33,
34,
33,
34,
33,
30,
31,
30,
32,
30,
32,
31,
33,
29,
31,
31,
30,
30,
30,
29,
29,
30,
30,
32,
30,
31,
31,
31,
30,
32,
32,
32,
33,
34,
34,
33,
33,
34,
35,
34,
34,
34,
36,
36,
36,
37,
37,
39,
40,
40,
40,
40,
42,
43,
42,
44,
44,
44,
42,
41,
41,
40,
40,
40,
42,
42,
40,
43,
43,
43,
44,
43,
41,
41,
40,
41,
40,
40,
39,
43,
41,
42,
41,
40,
41,
41,
41,
41,
39,
38,
38,
36,
34,
38,
37,
33,
34,
33,
33,
33,
33,
32,
31,
31,
30,
29,
29,
28,
27,
27,
27,
27,
23,
25,
24,
24,
23,
22,
22,
21,
21,
20,
19,
18,
18,
20,
18,
18,
17,
16,
16,
15,
14,
15,
15,
14,
14,
14,
13,
12,
12,
12,
11,
11,
11,
11,
10,
10,
9,
9,
9,
9,
7,
8,
7,
7,
7,
6,
6,
6,
6,
5,
5,
5,
4,
4,
3,
3,
3,
3,
2,
3,
3,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
2,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
3,
3,
2,
2,
3,
3,
2,
2,
2,
1,
3,
3,
2,
2,
2,
2,
2,
3,
2,
2,
3,
2,
2,
3,
4,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
4,
4,
5,
4,
4,
4,
5,
5,
3,
4,
4,
4,
5,
4,
5,
4,
3,
4,
5,
4,
3,
3,
4,
4,
4,
2,
4,
5,
3,
4,
3,
4,
2,
3,
2,
2,
2,
3,
4,
3,
3,
2,
2,
3,
3,
2,
2,
2,
1,
2,
2,
1,
1,
2,
2,
1,
1,
1,
1,
2,
1,
1,
0,
0,
1,
1,
1,
1,
1,
0,
0,
1,
0,
0,
0,
0,
1,
0,
0,
1,
1,
0,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
1,
1,
1,
0,
0,
0,
1,
1,
1,
2,
1,
1,
1,
0,
2,
1,
2,
7,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
1,
1,
0,
0,
0,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
2
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
337
],
[
339,
339
],
[
603,
883
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
0,
0,
0,
1,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
0,
1,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
3,
3,
3,
3,
4,
4,
4,
4,
5,
5,
5,
6,
6,
6,
6,
6,
7,
7,
7,
7,
8,
8,
8,
8,
8,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
8,
8,
8,
8,
8,
8,
7,
7,
7,
7,
6,
6,
6,
6,
5,
5,
5,
5,
5,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
2,
1,
1,
1,
1,
2,
1,
1,
2
] | {
"1. Frame Length": "The total frame length is: 423.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
0,
0,
0,
1,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
0,
1,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
3,
3,
3,
3,
4,
4,
4,
4,
5,
5,
5,
6,
6,
6,
6,
6,
7,
7,
7,
7,
8,
8,
8,
8,
8,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
8,
8,
8,
8,
8,
8,
7,
7,
7,
7,
6,
6,
6,
6,
5,
5,
5,
5,
5,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
2,
1,
1,
1,
1,
2,
1,
1,
2
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
278,
306
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
0,
0,
0,
1,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
0,
1,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
3,
3,
3,
3,
4,
4,
4,
4,
5,
5,
5,
6,
6,
6,
6,
6,
7,
7,
7,
7,
8,
8,
8,
8,
8,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
9,
8,
8,
8,
8,
8,
8,
7,
7,
7,
7,
6,
6,
6,
6,
5,
5,
5,
5,
5,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
2,
1,
1,
1,
1,
2,
1,
1,
2
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
94
],
[
102,
103
],
[
227,
252
],
[
342,
366
],
[
368,
391
],
[
393,
399
],
[
411,
413
],
[
415,
418
],
[
420,
421
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
6,
6,
7,
7,
8,
9,
10,
10,
11,
12,
12,
13,
14,
15,
16,
16,
15,
16,
17,
17,
18,
20,
19,
19,
19,
19,
19,
20,
20,
21,
20,
19,
17,
17,
17,
16,
16,
15,
14,
13,
12,
11,
10,
9,
8,
8,
7,
6,
10,
6,
5,
5,
4,
3,
3,
2,
2,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
3,
4,
5,
6,
6,
7,
12,
8,
8,
8,
9,
10,
11,
11,
12,
12,
12,
13,
14,
14,
15,
15,
16,
16,
16,
16,
17,
17,
18,
19,
19,
19,
19,
18,
18,
17,
18,
18,
17,
17,
16,
15,
15,
14,
13,
12,
11,
10,
8,
7,
6,
6,
5,
4,
3,
2,
2,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
2,
2,
2,
2,
1,
1,
1,
1,
1,
2,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0
] | {
"1. Frame Length": "The total frame length is: 469.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
6,
6,
7,
7,
8,
9,
10,
10,
11,
12,
12,
13,
14,
15,
16,
16,
15,
16,
17,
17,
18,
20,
19,
19,
19,
19,
19,
20,
20,
21,
20,
19,
17,
17,
17,
16,
16,
15,
14,
13,
12,
11,
10,
9,
8,
8,
7,
6,
10,
6,
5,
5,
4,
3,
3,
2,
2,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
3,
4,
5,
6,
6,
7,
12,
8,
8,
8,
9,
10,
11,
11,
12,
12,
12,
13,
14,
14,
15,
15,
16,
16,
16,
16,
17,
17,
18,
19,
19,
19,
19,
18,
18,
17,
18,
18,
17,
17,
16,
15,
15,
14,
13,
12,
11,
10,
8,
7,
6,
6,
5,
4,
3,
2,
2,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
2,
2,
2,
2,
1,
1,
1,
1,
1,
2,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
95,
111
],
[
170,
183
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
4,
5,
5,
6,
6,
7,
7,
8,
9,
10,
10,
11,
12,
12,
13,
14,
15,
16,
16,
15,
16,
17,
17,
18,
20,
19,
19,
19,
19,
19,
20,
20,
21,
20,
19,
17,
17,
17,
16,
16,
15,
14,
13,
12,
11,
10,
9,
8,
8,
7,
6,
10,
6,
5,
5,
4,
3,
3,
2,
2,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
3,
4,
5,
6,
6,
7,
12,
8,
8,
8,
9,
10,
11,
11,
12,
12,
12,
13,
14,
14,
15,
15,
16,
16,
16,
16,
17,
17,
18,
19,
19,
19,
19,
18,
18,
17,
18,
18,
17,
17,
16,
15,
15,
14,
13,
12,
11,
10,
8,
7,
6,
6,
5,
4,
3,
2,
2,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
2,
2,
2,
2,
1,
1,
1,
1,
1,
2,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
74
],
[
129,
145
],
[
197,
468
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
0,
0,
0,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
6,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
8,
8,
8,
8,
8,
9,
9,
9,
10,
10,
10,
11,
11,
11,
12,
12,
13,
13,
14,
14,
14,
16,
15,
16,
16,
17,
17,
18,
18,
19,
20,
20,
20,
21,
21,
21,
21,
22,
21,
21,
21,
21,
21,
22,
23,
24,
27,
30,
33,
37,
40,
44,
48,
51,
41,
58,
61,
63,
66,
68,
70,
72,
73,
74,
74,
74,
73,
71,
69,
67,
65,
63,
61,
60,
58,
57,
56,
55,
54,
52,
51,
49,
47,
46,
45,
44,
44,
43,
43,
44,
44,
45,
45,
46,
48,
49,
50,
51,
53,
54,
55,
57,
58,
60,
62,
64,
65,
66,
67,
69,
70,
72,
74,
76,
78,
78,
73,
67,
62,
61,
61,
60,
53,
46,
38,
33,
24,
31,
29,
27,
24,
22,
21,
21,
22,
23,
24,
25,
20,
27,
28,
28,
29,
29,
29,
29,
29,
29,
28,
28,
27,
26,
25,
24,
23,
22,
21,
20,
19,
18,
17,
16,
15,
14,
13,
12,
12,
11,
11,
10,
10,
9,
9,
8,
8,
8,
8,
7,
7,
7,
7,
7,
6,
6,
6,
5,
5,
5,
5,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
0,
0,
0,
0,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0
] | {
"1. Frame Length": "The total frame length is: 586.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
0,
0,
0,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
6,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
8,
8,
8,
8,
8,
9,
9,
9,
10,
10,
10,
11,
11,
11,
12,
12,
13,
13,
14,
14,
14,
16,
15,
16,
16,
17,
17,
18,
18,
19,
20,
20,
20,
21,
21,
21,
21,
22,
21,
21,
21,
21,
21,
22,
23,
24,
27,
30,
33,
37,
40,
44,
48,
51,
41,
58,
61,
63,
66,
68,
70,
72,
73,
74,
74,
74,
73,
71,
69,
67,
65,
63,
61,
60,
58,
57,
56,
55,
54,
52,
51,
49,
47,
46,
45,
44,
44,
43,
43,
44,
44,
45,
45,
46,
48,
49,
50,
51,
53,
54,
55,
57,
58,
60,
62,
64,
65,
66,
67,
69,
70,
72,
74,
76,
78,
78,
73,
67,
62,
61,
61,
60,
53,
46,
38,
33,
24,
31,
29,
27,
24,
22,
21,
21,
22,
23,
24,
25,
20,
27,
28,
28,
29,
29,
29,
29,
29,
29,
28,
28,
27,
26,
25,
24,
23,
22,
21,
20,
19,
18,
17,
16,
15,
14,
13,
12,
12,
11,
11,
10,
10,
9,
9,
8,
8,
8,
8,
7,
7,
7,
7,
7,
6,
6,
6,
5,
5,
5,
5,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
0,
0,
0,
0,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
235,
249
],
[
283,
295
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
0,
0,
0,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
3,
3,
3,
3,
3,
4,
4,
4,
4,
5,
5,
5,
5,
5,
5,
5,
6,
5,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
7,
7,
7,
7,
7,
7,
8,
8,
8,
8,
8,
9,
9,
9,
10,
10,
10,
11,
11,
11,
12,
12,
13,
13,
14,
14,
14,
16,
15,
16,
16,
17,
17,
18,
18,
19,
20,
20,
20,
21,
21,
21,
21,
22,
21,
21,
21,
21,
21,
22,
23,
24,
27,
30,
33,
37,
40,
44,
48,
51,
41,
58,
61,
63,
66,
68,
70,
72,
73,
74,
74,
74,
73,
71,
69,
67,
65,
63,
61,
60,
58,
57,
56,
55,
54,
52,
51,
49,
47,
46,
45,
44,
44,
43,
43,
44,
44,
45,
45,
46,
48,
49,
50,
51,
53,
54,
55,
57,
58,
60,
62,
64,
65,
66,
67,
69,
70,
72,
74,
76,
78,
78,
73,
67,
62,
61,
61,
60,
53,
46,
38,
33,
24,
31,
29,
27,
24,
22,
21,
21,
22,
23,
24,
25,
20,
27,
28,
28,
29,
29,
29,
29,
29,
29,
28,
28,
27,
26,
25,
24,
23,
22,
21,
20,
19,
18,
17,
16,
15,
14,
13,
12,
12,
11,
11,
10,
10,
9,
9,
8,
8,
8,
8,
7,
7,
7,
7,
7,
6,
6,
6,
5,
5,
5,
5,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
0,
0,
0,
0,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
198
],
[
200,
200
],
[
340,
585
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
46,
46,
45,
45,
44,
45,
44,
44,
44,
44,
44,
44,
43,
43,
43,
43,
43,
43,
43,
43,
42,
42,
42,
42,
42,
42,
42,
42,
41,
41,
41,
41,
41,
41,
41,
41,
41,
40,
40,
40,
40,
40,
40,
40,
40,
39,
39,
39,
39,
39,
39,
39,
39,
39,
39,
39,
39,
39,
38,
38,
38,
38,
38,
38,
38,
38,
38,
38,
38,
37,
37,
37,
37,
37,
37,
37,
37,
37,
37,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
35,
35,
35,
35,
35,
35,
35,
35,
35,
35,
34,
34,
34,
34,
34,
34,
34,
34,
34,
34,
33,
33,
33,
33,
33,
33,
33,
33,
32,
32,
32,
32,
32,
32,
32,
32,
31,
31,
31,
31,
31,
31,
31,
31,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
29,
29,
29,
29,
29,
29,
29,
29,
29,
29,
28,
28,
28,
28,
28,
28,
28,
28,
28,
28,
28,
28,
27,
27,
27,
27,
27,
27,
27,
27,
27,
27,
27,
26,
26,
26,
26,
26,
26,
26,
26,
26,
26,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
24,
24,
24,
24,
24,
24,
24,
23,
23,
23,
23,
23,
23,
23,
23,
23,
22,
22,
22,
22,
22,
22,
22,
22,
21,
21,
21,
21,
21,
21,
21,
21,
21,
20,
20,
20,
20,
20,
20,
20,
19,
19,
19,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
17,
17,
17,
17,
17,
17,
16,
16,
16,
16,
16,
16,
16,
15,
15,
15,
15,
15,
15,
15,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
13,
13,
13,
13,
13,
13,
13,
13,
13,
12,
12,
12,
12,
12,
12,
11,
11,
11,
11,
11,
11,
11,
11,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
11,
11,
11,
11,
11,
11,
11,
12,
12,
12,
13,
13,
13,
14,
14,
14,
15,
15,
15,
16,
16,
16,
17,
17,
17,
17,
17,
17,
18,
18,
18,
18,
17,
17,
16,
16,
15,
14,
13,
12,
12,
12,
11,
11,
10,
10,
10,
9,
9,
9,
9,
9,
9,
9,
8,
8,
8,
8,
8,
8,
8,
7,
8,
7,
7,
7,
7
] | {
"1. Frame Length": "The total frame length is: 399.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
46,
46,
45,
45,
44,
45,
44,
44,
44,
44,
44,
44,
43,
43,
43,
43,
43,
43,
43,
43,
42,
42,
42,
42,
42,
42,
42,
42,
41,
41,
41,
41,
41,
41,
41,
41,
41,
40,
40,
40,
40,
40,
40,
40,
40,
39,
39,
39,
39,
39,
39,
39,
39,
39,
39,
39,
39,
39,
38,
38,
38,
38,
38,
38,
38,
38,
38,
38,
38,
37,
37,
37,
37,
37,
37,
37,
37,
37,
37,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
35,
35,
35,
35,
35,
35,
35,
35,
35,
35,
34,
34,
34,
34,
34,
34,
34,
34,
34,
34,
33,
33,
33,
33,
33,
33,
33,
33,
32,
32,
32,
32,
32,
32,
32,
32,
31,
31,
31,
31,
31,
31,
31,
31,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
29,
29,
29,
29,
29,
29,
29,
29,
29,
29,
28,
28,
28,
28,
28,
28,
28,
28,
28,
28,
28,
28,
27,
27,
27,
27,
27,
27,
27,
27,
27,
27,
27,
26,
26,
26,
26,
26,
26,
26,
26,
26,
26,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
24,
24,
24,
24,
24,
24,
24,
23,
23,
23,
23,
23,
23,
23,
23,
23,
22,
22,
22,
22,
22,
22,
22,
22,
21,
21,
21,
21,
21,
21,
21,
21,
21,
20,
20,
20,
20,
20,
20,
20,
19,
19,
19,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
17,
17,
17,
17,
17,
17,
16,
16,
16,
16,
16,
16,
16,
15,
15,
15,
15,
15,
15,
15,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
13,
13,
13,
13,
13,
13,
13,
13,
13,
12,
12,
12,
12,
12,
12,
11,
11,
11,
11,
11,
11,
11,
11,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
11,
11,
11,
11,
11,
11,
11,
12,
12,
12,
13,
13,
13,
14,
14,
14,
15,
15,
15,
16,
16,
16,
17,
17,
17,
17,
17,
17,
18,
18,
18,
18,
17,
17,
16,
16,
15,
14,
13,
12,
12,
12,
11,
11,
10,
10,
10,
9,
9,
9,
9,
9,
9,
9,
8,
8,
8,
8,
8,
8,
8,
7,
8,
7,
7,
7,
7
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
0,
78
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
46,
46,
45,
45,
44,
45,
44,
44,
44,
44,
44,
44,
43,
43,
43,
43,
43,
43,
43,
43,
42,
42,
42,
42,
42,
42,
42,
42,
41,
41,
41,
41,
41,
41,
41,
41,
41,
40,
40,
40,
40,
40,
40,
40,
40,
39,
39,
39,
39,
39,
39,
39,
39,
39,
39,
39,
39,
39,
38,
38,
38,
38,
38,
38,
38,
38,
38,
38,
38,
37,
37,
37,
37,
37,
37,
37,
37,
37,
37,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
36,
35,
35,
35,
35,
35,
35,
35,
35,
35,
35,
34,
34,
34,
34,
34,
34,
34,
34,
34,
34,
33,
33,
33,
33,
33,
33,
33,
33,
32,
32,
32,
32,
32,
32,
32,
32,
31,
31,
31,
31,
31,
31,
31,
31,
30,
30,
30,
30,
30,
30,
30,
30,
30,
30,
29,
29,
29,
29,
29,
29,
29,
29,
29,
29,
28,
28,
28,
28,
28,
28,
28,
28,
28,
28,
28,
28,
27,
27,
27,
27,
27,
27,
27,
27,
27,
27,
27,
26,
26,
26,
26,
26,
26,
26,
26,
26,
26,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
25,
24,
24,
24,
24,
24,
24,
24,
23,
23,
23,
23,
23,
23,
23,
23,
23,
22,
22,
22,
22,
22,
22,
22,
22,
21,
21,
21,
21,
21,
21,
21,
21,
21,
20,
20,
20,
20,
20,
20,
20,
19,
19,
19,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
17,
17,
17,
17,
17,
17,
16,
16,
16,
16,
16,
16,
16,
15,
15,
15,
15,
15,
15,
15,
14,
14,
14,
14,
14,
14,
14,
14,
14,
14,
13,
13,
13,
13,
13,
13,
13,
13,
13,
12,
12,
12,
12,
12,
12,
11,
11,
11,
11,
11,
11,
11,
11,
11,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
10,
11,
11,
11,
11,
11,
11,
11,
11,
12,
12,
12,
13,
13,
13,
14,
14,
14,
15,
15,
15,
16,
16,
16,
17,
17,
17,
17,
17,
17,
18,
18,
18,
18,
17,
17,
16,
16,
15,
14,
13,
12,
12,
12,
11,
11,
10,
10,
10,
9,
9,
9,
9,
9,
9,
9,
8,
8,
8,
8,
8,
8,
8,
7,
8,
7,
7,
7,
7
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
286,
347
],
[
369,
398
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
13,
13,
15,
16,
15,
15,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
17,
17,
17,
17,
17,
17,
18,
18,
19,
19,
19,
20,
20,
21,
21,
22,
22,
23,
23,
24,
24,
24,
24,
25,
24,
24,
24,
23,
22,
21,
21,
20,
19,
19,
18,
18,
17,
17,
17,
17,
17,
17,
17,
17,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
19,
20,
20,
20,
21,
21,
21,
22,
23,
23,
24,
24,
25,
25,
26,
27,
27,
28,
28,
28,
28,
27,
26,
25,
24,
23,
22,
21,
21,
20,
20,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
19,
19,
19,
19,
19,
20,
20,
20,
20,
21,
21,
21,
22,
22,
22,
23,
23,
24,
25,
25,
26,
26,
26,
26,
26,
26,
25,
24,
24,
23,
22,
21,
20,
20,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
19,
20,
20,
20,
21,
21,
22,
22,
23,
24,
24,
25,
25,
26,
27,
27,
28,
28,
28,
28,
27,
27,
26,
25,
25,
24,
23,
22,
21,
21,
21,
20,
20,
20,
20,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
19,
19,
19,
19,
19,
19,
19,
20,
20,
20,
20,
20,
20,
20,
21,
21,
21,
21,
22,
22,
23,
23,
24,
24,
25,
25,
26,
27,
27,
28,
28,
28,
28,
27,
27,
26,
25,
25,
24,
23,
22,
22,
21,
21,
20,
20,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
20,
19,
19,
20,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19
] | {
"1. Frame Length": "The total frame length is: 401.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
13,
13,
15,
16,
15,
15,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
17,
17,
17,
17,
17,
17,
18,
18,
19,
19,
19,
20,
20,
21,
21,
22,
22,
23,
23,
24,
24,
24,
24,
25,
24,
24,
24,
23,
22,
21,
21,
20,
19,
19,
18,
18,
17,
17,
17,
17,
17,
17,
17,
17,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
19,
20,
20,
20,
21,
21,
21,
22,
23,
23,
24,
24,
25,
25,
26,
27,
27,
28,
28,
28,
28,
27,
26,
25,
24,
23,
22,
21,
21,
20,
20,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
19,
19,
19,
19,
19,
20,
20,
20,
20,
21,
21,
21,
22,
22,
22,
23,
23,
24,
25,
25,
26,
26,
26,
26,
26,
26,
25,
24,
24,
23,
22,
21,
20,
20,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
19,
20,
20,
20,
21,
21,
22,
22,
23,
24,
24,
25,
25,
26,
27,
27,
28,
28,
28,
28,
27,
27,
26,
25,
25,
24,
23,
22,
21,
21,
21,
20,
20,
20,
20,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
19,
19,
19,
19,
19,
19,
19,
20,
20,
20,
20,
20,
20,
20,
21,
21,
21,
21,
22,
22,
23,
23,
24,
24,
25,
25,
26,
27,
27,
28,
28,
28,
28,
27,
27,
26,
25,
25,
24,
23,
22,
22,
21,
21,
20,
20,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
20,
19,
19,
20,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
47,
57
],
[
119,
136
],
[
194,
208
],
[
268,
286
],
[
340,
359
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
13,
13,
15,
16,
15,
15,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
16,
17,
17,
17,
17,
17,
17,
18,
18,
19,
19,
19,
20,
20,
21,
21,
22,
22,
23,
23,
24,
24,
24,
24,
25,
24,
24,
24,
23,
22,
21,
21,
20,
19,
19,
18,
18,
17,
17,
17,
17,
17,
17,
17,
17,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
19,
20,
20,
20,
21,
21,
21,
22,
23,
23,
24,
24,
25,
25,
26,
27,
27,
28,
28,
28,
28,
27,
26,
25,
24,
23,
22,
21,
21,
20,
20,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
19,
19,
19,
19,
19,
20,
20,
20,
20,
21,
21,
21,
22,
22,
22,
23,
23,
24,
25,
25,
26,
26,
26,
26,
26,
26,
25,
24,
24,
23,
22,
21,
20,
20,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
18,
19,
19,
19,
19,
19,
20,
20,
20,
21,
21,
22,
22,
23,
24,
24,
25,
25,
26,
27,
27,
28,
28,
28,
28,
27,
27,
26,
25,
25,
24,
23,
22,
21,
21,
21,
20,
20,
20,
20,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
20,
19,
19,
19,
19,
19,
19,
19,
20,
20,
20,
20,
20,
20,
20,
21,
21,
21,
21,
22,
22,
23,
23,
24,
24,
25,
25,
26,
27,
27,
28,
28,
28,
28,
27,
27,
26,
25,
25,
24,
23,
22,
22,
21,
21,
20,
20,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
20,
19,
19,
20,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19,
19
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
29
]
]
}
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To calculate the frame length, count the total number of frames in the dataset. Each frame represents a data point collected over time. The total frame length gives the duration of the motion or activity being analyzed. In this dataset, the total frame length is determined by the number of entries in the data array. | [
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
3,
1,
2,
2,
3,
3,
4,
4,
4,
4,
5,
6,
6,
7,
8,
8,
9,
10,
10,
10,
11,
11,
11,
12,
13,
14,
13,
14,
16,
18,
18,
20,
22,
25,
26,
28,
30,
28,
27,
27,
28,
26,
26,
29,
34,
42,
49,
53,
63,
67,
73,
76,
71,
69,
62,
59,
51,
49,
45,
46,
46,
48,
51,
53,
55,
62,
66,
69,
74,
62,
53,
54,
52,
46,
61,
44,
47,
48,
50,
49,
49,
51,
53,
52,
51,
50,
48,
48,
49,
49,
48,
43,
47,
51,
54,
57,
63,
71,
79,
86,
93,
103,
112,
113,
121,
126,
123,
117,
115,
107,
108,
102,
100,
100,
97,
99,
101,
101,
102,
103,
105,
109,
111,
114,
118,
116,
115,
100,
98,
89,
86,
87,
77,
75,
75,
73,
65,
56,
59,
68,
70,
67,
65,
82,
95,
109,
114,
117,
136,
131,
140,
141,
153,
151,
132,
131,
131,
142,
138,
133,
126,
115,
121,
123,
120,
119,
120,
125,
129,
131,
138,
140,
138,
140,
142,
142,
146,
153,
155,
82,
83,
107,
66,
70,
55,
44,
49,
48,
46,
51,
54,
56,
55,
36,
51,
43,
46,
42,
42,
39,
30,
33,
30,
28,
28,
27,
24,
26,
23,
24,
21,
20,
20,
18,
20,
17,
19,
16,
15,
14,
13,
13,
11,
11,
10,
10,
9,
8,
9,
8,
7,
7,
6,
6,
6,
6,
5,
6,
5,
4,
5,
4,
4,
4,
4,
4,
3,
4,
3,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
1,
1,
1,
1,
2,
1,
2,
2,
1,
1,
1,
1,
1
] | {
"1. Frame Length": "The total frame length is: 338.",
"2. Local Maxima": null,
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local maxima, we identify the ranges where the values reach a peak within the dataset. A local maximum is a point where the value is higher than its neighboring values. This indicates periods of high activity or dynamic movement. The detection is based on a threshold percentage (e.g., 80% of the maximum value) to focus on the most significant peaks. The output lists the frame ranges where these peaks occur and their respective values. | [
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
3,
1,
2,
2,
3,
3,
4,
4,
4,
4,
5,
6,
6,
7,
8,
8,
9,
10,
10,
10,
11,
11,
11,
12,
13,
14,
13,
14,
16,
18,
18,
20,
22,
25,
26,
28,
30,
28,
27,
27,
28,
26,
26,
29,
34,
42,
49,
53,
63,
67,
73,
76,
71,
69,
62,
59,
51,
49,
45,
46,
46,
48,
51,
53,
55,
62,
66,
69,
74,
62,
53,
54,
52,
46,
61,
44,
47,
48,
50,
49,
49,
51,
53,
52,
51,
50,
48,
48,
49,
49,
48,
43,
47,
51,
54,
57,
63,
71,
79,
86,
93,
103,
112,
113,
121,
126,
123,
117,
115,
107,
108,
102,
100,
100,
97,
99,
101,
101,
102,
103,
105,
109,
111,
114,
118,
116,
115,
100,
98,
89,
86,
87,
77,
75,
75,
73,
65,
56,
59,
68,
70,
67,
65,
82,
95,
109,
114,
117,
136,
131,
140,
141,
153,
151,
132,
131,
131,
142,
138,
133,
126,
115,
121,
123,
120,
119,
120,
125,
129,
131,
138,
140,
138,
140,
142,
142,
146,
153,
155,
82,
83,
107,
66,
70,
55,
44,
49,
48,
46,
51,
54,
56,
55,
36,
51,
43,
46,
42,
42,
39,
30,
33,
30,
28,
28,
27,
24,
26,
23,
24,
21,
20,
20,
18,
20,
17,
19,
16,
15,
14,
13,
13,
11,
11,
10,
10,
9,
8,
9,
8,
7,
7,
6,
6,
6,
6,
5,
6,
5,
4,
5,
4,
4,
4,
4,
4,
3,
4,
3,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
1,
1,
1,
1,
2,
1,
2,
2,
1,
1,
1,
1,
1
] | {
"1. Frame Length": null,
"2. Local Maxima": {
"frames": [
[
171,
171
],
[
214,
226
],
[
233,
244
]
]
},
"3. Local Minima": null
} |
Center velocity represents the speed of movement of the center of gravity of the body. Near the maximum value, the faster the center of the body moves, the closer to the minimum value, the slower the center of the body moves. Specifically, a peak value of 1 corresponds to actions like jumping, 0.6 to jumps within specific actions like ballet jumps or cartwheels, 0.4 to sitting, and 0.2 to walking.
To find the local minima, we identify the ranges where the values reach a low point within the dataset. A local minimum is a point where the value is lower than its neighboring values. This indicates periods of less activity or reduced movement. The detection is based on a threshold percentage (e.g., 20% above the minimum value) to focus on the most significant dips. The output lists the frame ranges where these dips occur and their respective values. | [
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
3,
1,
2,
2,
3,
3,
4,
4,
4,
4,
5,
6,
6,
7,
8,
8,
9,
10,
10,
10,
11,
11,
11,
12,
13,
14,
13,
14,
16,
18,
18,
20,
22,
25,
26,
28,
30,
28,
27,
27,
28,
26,
26,
29,
34,
42,
49,
53,
63,
67,
73,
76,
71,
69,
62,
59,
51,
49,
45,
46,
46,
48,
51,
53,
55,
62,
66,
69,
74,
62,
53,
54,
52,
46,
61,
44,
47,
48,
50,
49,
49,
51,
53,
52,
51,
50,
48,
48,
49,
49,
48,
43,
47,
51,
54,
57,
63,
71,
79,
86,
93,
103,
112,
113,
121,
126,
123,
117,
115,
107,
108,
102,
100,
100,
97,
99,
101,
101,
102,
103,
105,
109,
111,
114,
118,
116,
115,
100,
98,
89,
86,
87,
77,
75,
75,
73,
65,
56,
59,
68,
70,
67,
65,
82,
95,
109,
114,
117,
136,
131,
140,
141,
153,
151,
132,
131,
131,
142,
138,
133,
126,
115,
121,
123,
120,
119,
120,
125,
129,
131,
138,
140,
138,
140,
142,
142,
146,
153,
155,
82,
83,
107,
66,
70,
55,
44,
49,
48,
46,
51,
54,
56,
55,
36,
51,
43,
46,
42,
42,
39,
30,
33,
30,
28,
28,
27,
24,
26,
23,
24,
21,
20,
20,
18,
20,
17,
19,
16,
15,
14,
13,
13,
11,
11,
10,
10,
9,
8,
9,
8,
7,
7,
6,
6,
6,
6,
5,
6,
5,
4,
5,
4,
4,
4,
4,
4,
3,
4,
3,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
1,
1,
1,
1,
2,
1,
2,
2,
1,
1,
1,
1,
1
] | {
"1. Frame Length": null,
"2. Local Maxima": null,
"3. Local Minima": {
"frames": [
[
0,
109
],
[
266,
266
],
[
268,
337
]
]
}
} |